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Can Plagiarism Checkers Detect Translated Text?

3-minute read

• 6th August 2023

If you’re a student or researcher, then you know how important it is to properly credit your sources and avoid plagiarism. But what should you do when your research includes translated text ?

In this post, we’ll discuss plagiarism across more than one language, whether plagiarism checkers can detect translated text, and how to avoid plagiarism in your work. Keep reading for more.

What Is Cross-Language Plagiarism?

Cross-language plagiarism, also known as multilingual plagiarism, occurs when someone takes content from a source in one language and translates it into another language without proper attribution or citation (i.e., presenting it as their original work). This can include self-plagiarism – using translations of your own previously published work.

While any form of plagiarism is serious and a breach of ethics, many times plagiarism is unintentional. To avoid unintentionally plagiarizing someone else’s work, it’s a good idea to use an online plagiarism detector, regardless of your field of study.

What Is a Plagiarism Checker?

Plagiarism checkers, like those offered by Turnitin or EasyBib , are a great way to check your work for plagiarized text before publication. They maintain a vast database of previously published content, including academic papers, articles, and websites. The tool compares the submitted text to the database to find potential matches.

Typically, plagiarism detectors will provide an originality score or percentage, indicating how much of the submitted text is considered original and how much is potentially plagiarized. Some may include additional information about the matched sources, such as the author or publication year.

If you use a plagiarism checker for your work, will it detect translated text? The answer – probably. If the translated text matches any previously published content in the same or another language, it will likely be flagged as potential plagiarism.

Some advanced plagiarism detection tools can recognize content that has been translated from one language to another. These tools use algorithms to identify similarities between the original text and its translated version. They can detect paraphrased or reworded content, even if it’s in a different language. Some plagiarism checkers even employ contextual analysis to determine whether a translated text is a legitimate adaptation or a case of plagiarism. They take into consideration factors such as the overall structure of the text and the presence of original ideas or insights.

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The effectiveness of plagiarism checkers can vary depending on how advanced the detection method is, and the specific techniques used in the translation. If the translation is significantly different from the original text or if it includes substantial changes and additions, it may not always trigger plagiarism detection.

How to Avoid Plagiarism

To avoid plagiarism (even unintentional plagiarism) when writing a research paper or essay, you can:

●  Summarize, paraphrase , and add your insights when incorporating ideas from a source.

●  Obtain permission to use published texts when necessary.

●  Use an online plagiarism checker.

●  Properly cite quoted and paraphrased sources, including translated sources, in the text and on a separate references page if necessary.

To ensure all your sources are properly cited according to your required referencing style, why not have your work professionally proofread? At Proofed, we can check that your work meets the proper citation guidelines. Send in your free sample today and see for yourself!

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Translation = plagiarism?

Manon is in the writing process of her thesis. She wondered: " I found an interesting text in a language other than English. If I translate it, should I mention the source?"

Summary:  In which language should i search on the web? Are you free in the translation? Why cite others’ sources?

1. In which language should I search on the web?

The search for information is becoming international!

Since the arrival of the Internet, knowledge sharing has become easier and automatic translators have made accessing it much easier. Some languages are richer than others in terms of web content , for example English is the most common language on the web and accounts for more than half of all Internet data.

"English accounting for 54 percent of the top 10 million websites." " Two Worlds: Languages IRL and Online " from the website statista.com

However, depending on the subject matter, it is a good strategy to explore these different avenues and languages in order to have an adequate overview of the subject you wish to address.

2. Are you free in the translation?

The information as it is found remains to be translated. The translation may deviate slightly from the original text to improve comprehension . If you are not bilingual, you can use different translation applications through open access sites such as Google translate  or  Deepl Translator . Word-for-word translation is not always accurate and if you have any doubts, you can quote the sentence in its original language with quotation marks + the author and explain its meaning . You can also paraphrase the information found in your own words, without quoting the text but still mentioning the author .

You are therefore free to translate information found in foreign languages. However, it is important to cite your sources .

3. Why cite others’ sources?

For further reflection  .

When the reader is interested in a subject, they often want to deepen their knowledge . The reader of your work must have the opportunity to do so with the sources cited and your well-constructed bibliography .

"Readers can use the list of references to  explore a subject further and enrich their understanding . Indeed, readers can easily and quickly find the references for the works they would like to explore." " An effective bibliography: great, but how? " from Compilatio.

Real and concrete information

Where did this information come from? A magician's hat? From your girlfriend? Or a specific source? The source allows to validate the information presented and gives a real and concrete dimension to what you’ve written, thus making you more credible to the reader.

Expert position  

You have not created all the content of your work, and that is a fact. However, you did some research that led you to a deep understanding of the subject. This research is what makes you an expert on the presented subject, and it should be showcased.

"Have you considered this? By making the choice not to plagiarise and to provide your own ideas,  you yourself become an "inventor" " " Why is plagiarism prohibited? What are my incentives to respect copyright? " from Compilatio

Quiet conscience  

Doing a job that requires a lot of time and investment is always a little stressful. Save yourself the added stress of wondering if your proofreader will realize that some parts have been plagiarized and cite your sources . Build an effective bibliography and check your work with Compilatio Studium , the plagiarism detection and writing assistance software. You'll set your mind at ease, and will be better for it in the long run.

Specific questions during defense  

When it comes time for the oral defense of your thesis, dissertation, or assignment, the teachers will ask you specific questions . If you master your subject, it will only be a formality. But, if you have plagiarized an idea, that's when the teachers will expose you (if they haven't done so before). They will ask you for explanations to ensure that you fully understand what you have described in your brief.

"If you are not certain that you have fully grasped the author's concept, don't incorporate it in your project. You will have a hard time  putting it into your own words  and your teacher will quickly sense that you are uncomfortable with the theory, then will probably  ask you questions specifically on this point ." " The power of paraphrasing " Compilatio

Tribute to the original author  

Whether in their own language or not, the original author has made an effort to reflect and write and it is fair and honest to mention it to pay tribute to them. Furthermore, the law protects authors.

According to article L122-4 of the Intellectual Property Code: "Any representation or reproduction, in whole or in part, made without the consent of the author or his successors or assigns is unlawful. The same shall apply to translation, adaptation or transformation, arrangement or reproduction by any art or process whatsoever."

To answer Manon, translating without citing the original author is considered plagiarism and is called translingual plagiarism.

Sources:  " Two Worlds: Languages IRL and Online " Statista.com. 19/02/2019. Constulted on 17/03/2022. " Translation Plagiarism: burning issue in modern plagiarism detection " Medium.com. Consulted on 17/03/2022. For further more: " An effective bibliography: great, but h ow? " Compilatio, 17/02/2022. " The power of Paraphrasing " Compilatio, 08/03/2022. " Quotation rules to avoid plagiarism: how to properly cite your sources "  Compilatio, 28/01/2022.

Translation Plagiarism: A Modern Day Concern

May 27, 2021 | Content translation , Copywriting

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The growing threat of cross-language plagiarism and the challenges in its detection

What is cross-language plagiarism.

Cross-language plagiarism refers to the kind of plagiarism or cheating where the source content is in one language while the plagiarised content is in another. In other words, it is plagiarism by translation.

In recent years, this kind of plagiarism has been on the rise given the free and easy access to online resources and free-to-use translation tools. It has become increasingly simple for students and people in general, to access content from anywhere in the world irrespective of the language and reproduce it in a different language using translation tools.

Additionally, the growth in multi-lingual people has further led to an increase in cross-language plagiarism as many find it easy to read and research in one language whilst writing in another language.

Research by Chris Park (2003), Stevens and Stevens (1987), Davis et al. (1992), Love and Simmons (1998), Silverman (2002) and Straw (2002) point to a variety of factors that can lead to plagiarism – lack of understanding about what constitutes plagiarism, growing competition, poor time management, inadequate writing skills and lack of deterrence are some of them.

Can cross-language plagiarism be detected?

Cross-language plagiarism detection has largely been an unexplored domain. One of the main reasons for this is because detection of such instances of plagiarism is extremely difficult given that the original text is no longer in the same language as the re-produced text. Hence, traditional similarity or plagiarism detection solutions are unable to correctly identify this type of plagiarism.

However, in light of the growing threat to academic integrity from this type of plagiarism, it has become extremely important to find ways to detect and deter plagiarism by translation.

Researchers have now come up with different methods to estimate if two sets of texts written in different languages are essentially copies of each other. For example, a model proposed by Barron-Cedeno, based on statistical machine translation technology. Another model is MLPlag (2008), proposed by Ceska. In this method, translations are compared at document level. While progress has been made within the larger more commonly used languages, for less-resourced and remote languages, there is still much to be desired.

Solutions that help detect cross-language plagiarism

While it’s reassuring to see that progress is being made in this sphere, for most of us working in the education sector or in professions where we need to be able to detect plagiarism, what is key is access to a simple and efficient solution that is easy to use and works at the click of a button.

Ouriginal , a pioneer in text-matching and similarity-detection solutions, offers exactly this. Its Cross-Language Text Matching (CLTM) feature is now able to identify matching content that has been translated from one language to another using a proprietary algorithm. The highly specialized algorithm identifies segments of texts in different languages that appear to be similar. The algorithm then identifies sentences that contain these segments to check if the sentences themselves are translations of each other, thus detecting potential matches.

See the example below:

By comparing the words highlighted in red, our system was able to identify that the text in blue is a translation from Dutch.

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• Original article
• Open access
• Published: 19 December 2018

Paraphrasing tools, language translation tools and plagiarism: an exploratory study

• Felicity M. Prentice   ORCID: orcid.org/0000-0003-4962-7413 1 &
• Clare E. Kinden 1  

International Journal for Educational Integrity volume  14 , Article number:  11 ( 2018 ) Cite this article

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In a recent unit of study in an undergraduate Health Sciences pathway course, we identified a set of essays which exhibited similarity of content but demonstrated the use of bizarre and unidiomatic language. One of the distinct features of the essays was the inclusion of unusual synonyms in place of expected standard medical terminology.

We suspected the use of online paraphrasing tools, but were also interested in investigating the possibility of the use of online language translation tools. In order to test the outputs of these tools, we used as a seed document a corpus of text which had been provided to the students as prompt for the essay. This document was put through six free online paraphrasing tools and six separate iterative language translations through the online Google Translate™ tool.

The results demonstrated that free online paraphrasing tools did not identify medical terminology as standardised or accepted nomenclature and substituted synonyms, whereas Google Translate™ largely preserved medical terminology.

We believe that textual indicators such as the absence of standard discipline-based terminology may be of assistance in the identification of machine paraphrased text.

Introduction

Imagine you are reading a student’s essay and are confronted with the following sentence:

A situation that can give resistance and additionally generally safe for botches, and that inspects choices without assaulting the pride and nobility of the individual influencing them, to will prompt better natural decisions.

In an assessment task set for first year undergraduate Health Science students in a pathway program, an alarming proportion of submitted work, nearly 10%, demonstrated linguistic contortions similar to the example given. This led us to consider the following questions:

Were students using online paraphrasing tools to manipulate work which was written in English and which had not been authored by them?

Were students who had English as an Additional Language (EAL) composing work in their first language and then translating this through online language translation tools?

Are there indicators which can identify the use of on-line paraphrasing tools?

All examples of unusual writing provided in this article are indicative of the nature of the student writing encountered but have been altered to retain anonymity while preserving the features of the linguistic anomalies.

While standards of English expression may vary considerably in work submitted by students, it is becoming more common to encounter essays which display standards of writing well below that which is expected of students studying in Higher Education. When the student is from an English as an Additional Language (EAL) background, poor expression in written work has been attributed to lack of facility with the language, clumsy patchwriting, or the use of an online translation tool, such as Google Translate™ (n.d.) ( https://translate.google.com.au ). Mundt and Groves ( 2016 ) contend that when students use an online translation tool to convert their own work from their first language into English this may be considered demonstrative of poor academic practice, as they are not actively developing English language skills. However, as the original work is the result of the student’s own intellectual merit, it is contentious as to whether this qualifies as academic misconduct. In the case of the submissions we received there was reasonable suspicion that the text had not been subject to a language translation tool but had been reengineered by an English-to-English paraphrasing tool. This called into question the source of the original English text, and suggested there was evidence of a genuine breach of academic integrity.

Rogerson and McCarthy ( 2017 ) reported that their initial awareness of paraphrasing tools was through a casual comment by a student. In our case, the serendipitous discovery of online paraphrasing tools was made when one of the authors was following an online forum discussing cheating methods. Prior to this revelation, our assumptions as to the origin of incomprehensible student writing had been more naïve, our explanations being focussed around patchwriting and LOTE-to-English translation tools. However, when encountering the extent of the use of inappropriate synonyms in essays submitted for this particular assessment task, we were moved to examine the text more closely. A review of one or two essays rapidly escalated to the identification of a cluster of essays which bore remarkable similarity in the use of peculiar language, and in particular the inclusion of bizarre synonyms for standard recognised terminology within the health sciences discipline. Further to this, there was significant similarity in the structure of the essays, where the information, and even in-text citations, were provided in an identical sequence. In some cases, the Turnitin® (n.d.) similarity index identified a match between a number of essays, but other suspicious works resulted in an index of 0%. It became clear that paraphrasing tools were probably being used and that students were colluding to paraphrase each other’s essays.

The literature is replete with the lamentations of academics who feel that pursuing academic misconduct forces them in to the role of detective. Collecting evidence, analysing scenarios, motives and prior offences and operating in a quasi-judicial, if not criminological paradigm, does not sit well within the cultural norms of academia (Brimble and Stevenson-Clarke 2006 ; Burke and Sanney 2018 ; Coren 2011 ; Keith-Spiegel et al. 1998 ; Sutherland-Smith 2005 : Thomas and De Bruin 2012 ). Our experiences seemed to resonate so clearly with this sentiment to the point where we felt a profound urge to recreate a television crime show, with essays taped to the wall connected by string, surrounded by tacked-up maps and photographs of the suspects.

The breakthrough came when an essay was so alarmingly absurd that we were able to trace the origin to another student’s essay. The assessment task was to analyse and discuss a scenario regarding a young Indigenous man’s experiences in the Australian Health Care System.

One student included in their essay a description of a Computerised Axial Tomography (CAT) scan which had been plagiarised from a Wikipedia page. However, in transcribing how images were taken from various angles, they had misspelled the word ‘angles’ as ‘angels’. This spelling error had not caused concern, however work submitted by another student provided evidence that there was a curious literary connection between the essays. In this case the second student reported that the CAT Scan images were taken from various ‘Blessed Messengers’.

It was apparent that the second student had used a paraphrasing tool to ‘spin’, that is, to apply synonym substitution, to the essay obtained from their colleague.

Given the poor standard of the output, why would a student resort to using paraphrasing tools? Paraphrasing is a complex and demanding task, requiring students to demonstrate not only understanding of the meaning and purpose of the text, but also to find the linguistic facility to restate this meaning in new and original words, and specifically in the discourse of Academic English (Shi 2006 ).This task is difficult enough when performed in a first language, and the challenge is magnified when the student is from a non-English speaking background (Bretag 2007 ; Carroll 2015 ; Correa 2011 ; Handa and Power 2005 ; Marshall and Garry 2006 ).

Bretag ( 2007 ) describes two aspects of the acquisition of a second language. Basic interpersonal communication skills can be developed in approximately two years, however it is estimated to take five to ten years to develop cognitive academic linguistic proficiency which is necessary to function in an academic learning environment. Patchwriting is when students attempt to paraphrase a source by substituting synonyms in passages while retaining too closely the voice of the original writer (Jamieson 2015 ). This may be classified as an intermediary stage of the development of academic linguistic proficiency representing a form of non-prototypical plagiarism (Pecorari 2003 ). As such, it may not be a deliberate or intentional breach of academic conduct. In students with EAL, the acquisition of the linguistic facility to represent the meaning of a text without resorting to reproducing the author’s actual words may take more than the few months that our students have been studying at an English-speaking University. However, in the cases under consideration, students did not attempt to manually re-engineer text in order to paraphrase but used an online paraphrasing tool to alter the entire corpus of the text. The original source text could be identified in many cases by a recognition of some structural features, for example, the reproduction of the scenario provided to the students.

Original One day, while Doug was out walking, he felt lightheaded and then lost consciousness and fell to the ground. He was brought to the Emergency Department of a major hospital by ambulance for assessment and investigation.

Post paraphrasing tool While one day on his walk Doug he felt bleary eyed and lost awareness and fell onto the ground. He was conveyed to the Emergency Department of the healing facility for significant appraisals and tests.

In some cases the original source was taken from the internet, notably Wikipedia, but in one instance the student lifted and paraphrased text taken directly from a file sharing site. The student did not provide an in-text citation, however the original source was identified by the student including the file sharing website address in the reference list. This has been referred to as illicit paraphrasing (Curtis and Vardanega 2016 ), and actions such as this may call into question the level of intentionality to deceive. The inclusion of a reference, albeit from an inappropriate source, may suggest the student was attempting to participate in the expectations of academic practice. Less generously, it may be assumed that copying material directly from a file sharing site, using a paraphrasing tool to deceive Turnitin® (n.d.) , and then submitting the work, even with a hopeful inclusion in the reference list, demonstrated an intentional breach of academic integrity.

• Patchwriting

Strategic word substitution has always been a feature of students’ attempts at paraphrasing, which Howard defined as patchwriting,

Copying from a source text and then deleting some words, altering grammatical structures, or plugging in one synonym for another. (Howard 1999 , p.xvii, in Jamieson 2015 )

While patchwriting by students has been characterised as poor academic practice, it is also seen as a preliminary effort to become familiar with the discourse of academic writing (Pecorari 2003 ).

In the essays considered in this exploratory study, we encountered examples of English expression which indicated that the EAL student was struggling to develop fluency, for example:

Doug leaves his home and move far away from his family to the city. There he have house with an unknown people and he have feeling of loneliness and unhappy. He is not able to get the job and had very small income. He was usually sad and feel bad in himself. It is all these factors lead to a poor health.

We were also able to recognise patchwriting in text that had been appropriated from multiple sources, and these incidents were usually identified by Turnitin® (n.d.) and exemplified by a ‘rainbow’ of colours in the similarity report demonstrating different sources. However, in the essays under investigation the text demonstrated the inclusion of synonyms resulting in writing which was largely unintelligible. Further to this, there had been no manipulation of the syntax of the sentences, which heightened the unidiomatic nature of the writing. Whereas in patchwriting synonyms are manually substituted by the student, online paraphrasing tools achieve this through an automatic function, and thus the question arises, as posited by Rogerson and McCarthy ( 2017 ), as to whether the use of online paraphrasing tools transcends patchwriting to become what Walker describes as illicit paraphrasing (in Pecorari 2003 , p.9).

Expected medical terminology

One of the most obvious issues we encountered in the essays was the use of synonyms for standard medical terminology. Standardised nomenclature and terminology are employed throughout health care to avoid ambiguity in documentation and communication. This provides the interface for meaningful and appropriate communication of medical, nursing and allied health information regarding patient care, and is an essential element of safety and standardisation in care (Pearson and Aromataris 2009 ). In addition, this terminology is used for medical information classification, and has been raised as a priority area in the introduction of electronic health records to ensure interoperability across systems and health disciplines (Monsen et al. 2010 ). The importance of employing correct and predictable terminology has been identified as paramount in avoiding adverse outcomes:

Current research indicates that ineffective communication among health care professionals is one of the leading causes of medical errors and patient harm. (Dingley et al. 2008 , p.1)

Therefore, the acquisition and correct contextual application of medical terminology is a fundamental part of learning in health sciences. Students are exposed to this terminology throughout their studies, and in the case of the assessment task under scrutiny, students were provided a scenario, or enquiry prompt, which included the standard discipline-based terminology (see Appendix ). The lack of standard medical terminology and the inclusion of unusual synonyms for this terminology was a significant feature of the essays. In the event that students were exhibiting difficulties with English expression, or were manually substituting synonyms as seen in patchwriting, it would be expected that the standard terminology would be preserved. This led us to suspect, and subsequently investigate, online paraphrasing tools.

• Paraphrasing tools

Spinning is a technique used to produce a new document, or documents, from an original text source by replacing words in such a way as to retain the overall meaning of the text, while avoiding machine-based text matching tools used to identify plagiarism. Machine based paraphrasing tools were developed to enable text spinning as a way of improving website rankings in Google search results and are part of a suite of search engine optimisation (SEO) techniques referred to as Black-Hat marketing. (Lancaster and Clarke 2009 ; Rogerson and McCarthy 2017 ; Zhang et al. 2014 ).

In web-based marketing the goal is to get the highest ranked place in a Google search index.

The Google search engine identifies and calculates the frequency of links between, and website traffic to, each website and ranks sites on the search results accordingly. In Black Hat marketing, the aim is to create sites including blogs, articles and webpages which provide multiple links to the target page, thus ensuring optimisation of the search engine results and a higher overall ranking (Bailey 2018 ).

Google search engines use word matching software which can recognise duplicate text and penalties are applied where this has been detected, hence the need to create paraphrasing tools which will instantly produce duplicate text material which cannot be detected. These paraphrasing tools were designed to hoodwink word matching software but were not intended to emulate human generated text. It is apparent that students are now using these tools to spin text from numerous original sources with the aim to deceive word matching software such as Turnitin® (n.d.) .

The free online automated paraphrasing tools rely principally on synonym substitution without altering the overall syntax of the sentence, resulting in language which is unidiomatic at best, incomprehensible at worst.

When Rogerson & McCarthy published in 2017, they reported that a simple Google search for paraphrasing tools resulted in over 550,000 hits. Our search in 2018 demonstrated a proliferation of paraphrasing sites resulting in over 3,320,000 hits. Cursory examination revealed that many are duplicate sites with the same tool offered under different names. Of greater concern is the increased juxtaposition of advertisements and links to essay purchasing services. Anticipating the vulnerability of the student, some sites offer a free paraphrasing tool but ensure the output is extremely poor.

For example, when the following sentence taken from the assessment scenario:

One day, while Doug was out walking, he felt lightheaded and then lost consciousness and fell to the ground. He was brought to the Emergency Department of a major hospital by ambulance for assessment and investigation.

is entered into a free online paraphrasing tool the following results were obtained:

Brace girl, stretch Doug was at large peripatetic, he felt lightheaded and fit lost consciousness and fell to the ground. He was debasement to the Danger Diversify of a chief sanatorium by ambulance for weight and criticism. Plagiarisma  http://plagiarisma.net/spinner.php

One sidereal day, while Doug was out walk, he felt lightheaded and then lost knowingness and downslope to the pulverization. He was brought to the Emergency Department of a major hospital by ambulance for assessment and probe. Rephraser  https://www.rephraser.net/instant-paraphrasing-tool/

This word salad is used to entice students into contract cheating, that is, outsourcing the assessment task to be completed by a third party (Lancaster and Clarke 2006 ). The sites provide a link to an essay writing service, in one case with a curiously poorly worded advertisement stating:

Aren’t satisfied with the results? But what to expect from the tool? Hire an expert for a quality rewording! Only $8.39/page. Paraphrasing Online  https://www.paraphrasingonline.com

Paraphrasing tools work by creating an intermediate text referred to as “spintax”, where a number of synonyms are provided for each selected word, for example the phrase:

the junior doctor in the rehabilitation centre prepared a discharge summary

is transformed into the intermediary spintax:

the {understudy specialist | lesser specialist | lesser pro} in the {recovery fixate | recovery focus | rebuilding centre} prepared a {release rundown | release report | blueprint}.

Based on a number of parameters, words can be substituted at varying rates within a sentence, however it is non-deterministic. Therefore, for the purpose of Black Hat marketing, this provides a vast number of permutations for the creation of articles which are sufficiently different from each other to evade detection by word matching software (Bailey 2018 ). This explains why students using paraphrasing tools may generate apparently different essays from a single seed document.

To create the spintax, a bank of potentially alternative terms is held in a synonym dictionary, which may be local to the paraphrasing tool, or held in cloud storage (Shahid et al. 2017 ; Zhang et al. 2014 ). In their study, Zhang et al. ( 2014 ) were able to access this dictionary and reverse engineer two paraphrasing tools (Plagiarisma and The Best Spinner) to establish which words are subject to synonym substitution, referred to as ‘mutables’ , and which words do not appear in the synonym dictionary and thus would not be included in the spintax, referred to as ‘immutables’ . This approach, referred to as DSpin, relies on comparing the unchanged text, or immutables, located within the spun text to the original text (Zhang et al. 2014 ). The match of immutable terms between documents (spun and original) will provide evidence of the source of the text. We became interested in the concept of immutable words and how these may be used to identify documents that had been machine paraphrased.

The paraphrasing tools that require a fee-based subscription provide a large number of parameters to manipulate the output, including the contents of the dictionary, the maximum number of synonyms used and replacement frequency, and the replacement of both single words and short phrases (Shahid et al. 2017 ). In this study we assumed that the students were accessing the fee free version of online paraphrasing tools and as a result the output of spinning was less subject to control resulting in more words treated as mutables and thus less discretionary synonym substitution.

As medical terminology is fundamental to the discourse of health sciences, it would be reasonable to classify these words as preferentially immutable . However, the paraphrasing tools do not have the capacity to recognise the significance and importance of these terms, and thus they are within the synonym dictionary as mutables and subject to synonym substitution.

Students in this unit of study are exposed to medical terminology throughout the curriculum, and it is emphasised that these terms are fundamental to the discourse and required for communication in health sciences. Hyland ( 2006 ) notes that becoming a member of a discourse community involves “learning to use language in disciplinary approved ways” (p.38). They are expected to use these terms, and it is clear in the rubric and marking guides that the assessment is aligned to the objective of the acquisition of this specialised language. The scenario provided in this assessment was rich and replete with the terminology, and there was ample opportunity for imitation and reproduction of the writing style and nomenclature. Therefore, the absence of the recognised terminology and the inclusion of unidiomatic and contextually invalid synonyms was particularly obvious to the readers.

Method of analysis

Identifying the use of paraphrasing tools.

It could be argued that the use of synonyms, in particular archaic or unidiomatic words and phrases, is a clear indicator that machine generated paraphrasing has been used. For example, in the papers submitted by students where the use of paraphrasing tools was suspected, the term aboriginal man was substituted with autochthonic person , the hospital became the mending office , the rehabilitation centre the recovery fixate , and the discharge summary the release precis .

In order to investigate the extent to which paraphrasing tools substituted recognised and expected medical terms for unusual synonyms, we selected three essays which we had identified as particularly unusual. We did not know the provenance of these essays, although there was structural evidence that they might have arisen from a single seed document which was an essay submitted by one student in the current cohort.

Table  1 shows the variation from the expected nomenclature.

Comparing online language translation and paraphrasing tools

Prior to learning of the existence of online paraphrasing tools, we had assumed that students were authoring work in their first language, and then using online translation tools to convert the text to English. Perhaps the most notable and available online free translation tool, Google Translate™, was made available as an online tool in 2006 using a statistical machine translation engine to translate text from one language, via English, on to the target language. In 2016 Google implemented a Neural Machine Translation engine, which has provided a more sophisticated and accurate output (Le and Schuster 2016 ). Given the idiomatic nature of language, errors may still occur where a word is translated into a synonym which may not be contextually valid.

To investigate the possibility that students had used Google Translate™, the scenario provided as the enquiry-based learning prompt was used as a seed document to ascertain the changes which might occur when paraphrasing tools and Google Translate™ were employed. The scenario ( Appendix ) was put through a number of paraphrasing tools, and in each case the standard medical terminology was consistently changed. When the scenario was put through Google Translate™, the terminology was changed only rarely.

The scenario document was subject to iterative language translation (Day et al. 2016 ). The text was entered into Google Translate™ for translation to a language other than English, and this translation was copied and re-entered to a refreshed Google Translate™ page for translation back into English. The target languages used were Arabic, Punjabi, Hindi, Chinese (Simplified), Chinese (Traditional) and Vietnamese. The languages were chosen as they represent the principal first languages of the EAL students enrolled in this subject.

The translations were of a generally good quality, displaying minor errors in tense and pronoun gender, but could be easily comprehended. The most accurate translations were Chinese (Simplified and Traditional) and Vietnamese, and the highest number of errors occurred in Arabic, Hindi and Punjabi. In the latter languages there were more substitutions for standardised health terms (Table  2 ).

The original scenario was then put through six paraphrasing tools selected as the top entries generated by a Google search using the term ‘paraphrasing tools’ . This technique follows that used by Rogerson and McCarthy ( 2017 ) based on the assumption that students would use a similar search strategy and select the sites listed at the top of the search results (Table  3 ).

It was not known whether these sites were using the same paraphrasing tool, however, given the multiple outputs available through non-discriminatory synonym substitution, there was ample opportunity for a diverse output.

The results from the output texts were analysed for synonym substitution of recognised and expected medical terminology, and this was compared to the outputs from the iterative language translation through Google Translate™. This technique was used for convenience purposes as the intention was to gain an overall impression of the extent to which medical terms were substituted by paraphrasing tools compared to Google Translate™. As can be seen from Table  4 , the proportion of substituted terms was significantly different. From the 21 standard medical terms there were 73 synonyms from the paraphrasing tools and 7 alternative terms from Google Translate™. Blank spaces in the table indicate that no alterative term was generated by Google Translate™.

Although it is not within the scope of this brief exploratory study to state that there is a measurable difference in synonym substitution between paraphrasing tools and Google Translate™, the above results give a general indication of the observable differences.

When determining whether there is a potential breach in academic integrity, it is important to distinguish between extremely poor English skills, the use of a LOTE-to-English translation device, and the generation of text through a paraphrasing tool. Carter and Inkpen ( 2012 , p.49) note “Machine translated text often seems to be intuitively identifiable by proficient speakers of a language”. If a student has used paraphrasing tools to alter a text to evade detection of plagiarism, then that act of evasion suggests that plagiarism has occurred. Word matching software such as Turnitin® (n.d.) has proven valuable in identifying replication of text from other sources. However, the very purpose of paraphrasing tools is to deceive software developed to detect plagiarism, and it is apparent that to date this strategy has been successful (Lancaster and Clarke 2009 ; Rogerson and McCarthy 2017 ; Shahid et al. 2017 ). Consequently, the burden of detection remains with the human reader who has to become increasing adept at spotting stylistic variations and any other flags relating to mechanisms that have been used to avoid detection (Gillam et al. 2010 ).

The method of detection we suggest, identifying the absence of expected nomenclature such as discipline based terminology, could be considered an extrinsic analysis of the text. The expected immutables of recognised medical terms are substituted with synonyms, and thus treated by the paraphrasing tools as mutables . The paraphrased text is compared to an ideal or external text, that is, the text containing the medical terminology which was expected by the assessor. Shahid et al. ( 2017 ) propose a method of intrinsic analysis of paraphrased text through stylometric analysis:

We observe that style, language, grammatical constructs, and certain linguistic expressions in spun documents deviate from a human author because spinning software introduce artefacts in their output which are specific to a text spinner. (p. 5)

The technique described in their study involves the application of a number of algorithms to a selected text which can lead to identification of the source text. This level of analysis is not currently available to academic staff seeking to identify plagiarism committed through the use of paraphrasing tools. However, Turnitin® (n.d.) is developing an Authorship Investigation tool which will use stylometric and forensic linguistic analysis to provide measurement parameters indicative of authorship of a text ( https://www.turnitin.com/solutions/authorship-investigation ,). Where there is suspicion that contract cheating has occurred, the Authorship Investigation tool will use examples of previous work submitted by a student to ascertain similarity of stylistic features to the work under suspicion. The premise is that a stylometric ‘fingerprint’ of the student’s literary style and expression can be used for comparison to submissions which may have been outsourced to another author. It is anticipated that this tool will be of potentially useful in determining whether a submission has hallmarks which distinguish it from other pieces of writing by the student, but it will not be possible to identify the author of the outsourced work.

In this exploratory study we identified linguistic features of spun text which indicated the use of paraphrasing tools. However, we were reliant on the curious case of the blessed messengers to point towards collusion. This was achieved through close collaboration by the marking staff, and until techniques for reverse engineering of paraphrased text become more widely available, “What ultimately leads to determinations of plagiarism is considerable manual analysis and subjective judgement” (Bretag and Mahmud 2009 , p.54).

Students, and in particular those from an EAL background, experience significant challenges in conforming to academic conventions such as paraphrasing. The availability of free online paraphrasing tools may appear to them as a realistic solution to these challenges despite the word salad which is created by these tools. Whereas EAL students who write original work in their first language and then use online translation tools to convert this to English may be demonstrating poor academic practice, it can be argued that the submitted work is a result of their own intellectual endeavours. Unfortunately, students who use paraphrasing tools to spin text from undisclosed sources, thus evading word matching software, have committed an overt act of academic dishonesty.

In academic writing in the health science discipline, there is an expectation that standard medical terminology will be used. We noted that absence of this in the students’ submissions and investigated the outputs of both paraphrasing tools and Google Translate™. We noted that paraphrasing tools are significantly more likely to substitute inappropriate synonyms for accepted medical nomenclature, whereas Google Translate™ largely preserved these terms intact.

When paraphrasing tools have been applied to text the output is frequently of such poor quality as to render the text unintelligible. We also noted the following features: the language generated will be notable for the use of unidiomatic words and phrases; expected vocabulary such as standard medical terminology will usually be substituted with inappropriate synonyms; word matching software, such as Turnitin® (n.d.) , may not recognise the re-engineered text from the source and thus provide a low similarity index which may not be indicative of the actual level of plagiarism.

When using online translation tools, such as Google Translate™, to convert text from a language other than English to English, there is less likelihood that discipline specific nomenclature, such as standard medical terminology, will be changed to the same extent as paraphrasing tools.

This study demonstrates that there are a number of distinct features which can be identified in the text generated by paraphrasing tools. Awareness of these features will assist in the process of detecting plagiarism. While the emphasis should be on supporting students to develop the skills required to paraphrase appropriately, identifying linguistic markers which provide evidence of the use of paraphrasing tools will be of benefit in the overall management of breaches of academic integrity.

Abbreviations

Computerised Axial Tomography Scan

English as an Additional Language

Emergency Department

Language other than English

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Scenario for assessment task

Doug is a nineteen year old aboriginal man who has had Type I Diabetes Mellitus since he was 13. Doug was born in a small town in a remote area of Victoria. Despite not completing Year 8, he decided to move away from his family to the city. He has not been able to get a job and has very little income. He misses his family, friends and community, but is determined that they not find out that he is unhappy. Doug has a history of homelessness but has been living for the past 2 weeks in a share house with people he doesn’t know well. Doug does not see the same doctor for his diabetes , he visits many different clinics , depending on where he is living at the time.

As a consequence of the fall, he sustained a head injury which resulted in severe and persistent headaches, loss of coordination and difficulty with walking. In the Emergency Department (ED) a number of tests were undertaken (including a CAT scan , blood sugar test and full examination). It was identified that prior to the fall he had experienced an episode of ‘ insulin shock ’.

Following an 8 h stay in the Emergency department , Doug was transferred to the Neurology ward for assessment and monitoring. In addition to the medical records available in the central electronic filing system, a member of the ED team provided a ‘ handover ’ to the Nurse Unit Manager of the Neurology Ward .

It was when he was on this ward that the nursing staff identified that Doug has limited knowledge of his diabetes including where to access support and advice, and how to monitor his glucose levels and adjust his insulin dose properly. A team consisting of nurses , the ward physiotherapist , a social worker , and a neurologist met on three occasions to discuss Doug’s case. They used the information from the Emergency Department admission , the assessments undertaken by the team of health professionals , and included Doug in all their decisions. They identified his issue with Diabetes management, but as this was a short admission to the Neurology Ward , they did not have the resources to follow this up. After a 4 day stay in the Neurology ward , the healthcare team decided that Doug would benefit from being transferred to a rehabilitation centre . A junior doctor who had just joined the ward was given the task of writing the discharge summary .

Doug was taken by patient transport to a rehabilitation centre which was not part of the acute hospital , but an independently run organisation. The brief discharge summary was sent with Doug describing the initial head injury and noting the need for ongoing therapy to assist his co-ordination and walking. While in the rehabilitation centre , Doug was assessed by the physiotherapist , occupational therapist , doctor , and of course the nursing staff who monitored Doug daily. They did not seek any additional information from the acute hospital , only using the discharge summary as a basis for Doug’s care. They did not formally meet, but they each wrote notes in Doug’s medical record .

On day six of his admission to the rehab centre , the Nurse Unit Manager observed Doug confidently walking in the ward corridor by himself. As a very experienced Rehab Nurse she decided that Doug could be discharged home based on his ability to independently toilet and ambulate. In addition, she was under considerable pressure by the senior management of the Rehab Centre to discharge patients to free up beds. Without consulting the other staff, the Nurse Unit Manager informed Doug that he was to be discharged the following day as he now appeared fine and had no consequences from his “little bump on the head.”

Doug was discharged the next day and returned to the house he was sharing. None of his housemates had even realised he had been away. Five days following his discharge home, Doug was again admitted to the ED by ambulance, having suffered a fall at home while trying to descend the stairs from the second floor where his bedroom was located. He fractured his left tibia as a result of the fall. He told the ED staff that he had not been eating well, but that he had still injected his usual insulin dose just prior to the fall.

(Bold and italics provided by authors to highlight standard medical terminology).

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Prentice, F.M., Kinden, C.E. Paraphrasing tools, language translation tools and plagiarism: an exploratory study. Int J Educ Integr 14 , 11 (2018). https://doi.org/10.1007/s40979-018-0036-7

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Plagiarism detection and prevention: a primer for researchers

Olena zimba.

1 Department of Internal Medicine No. 2, Danylo Halytsky Lviv National Medical University, Lviv, Ukraine

Armen Yuri Gasparyan

2 Departments of Rheumatology and Research and Development, Dudley Group NHS Foundation Trust (Teaching Trust of the University of Birmingham, UK), Russells Hall Hospital, Dudley, West Midlands, UK

Plagiarism is an ethical misconduct affecting the quality, readability, and trustworthiness of scholarly publications. Improving researcher awareness of plagiarism of words, ideas, and graphics is essential for avoiding unacceptable writing practices. Global editorial associations have publicized their statements on strategies to clean literature from redundant, stolen, and misleading information. Consulting related documents is advisable for upgrading author instructions and warning plagiarists of academic and other consequences of the unethical conduct. A lack of creative thinking and poor academic English skills are believed to compound most instances of redundant and “copy-and-paste” writing. Plagiarism detection software largely relies on reporting text similarities. However, manual checks are required to reveal inappropriate referencing, copyright violations, and substandard English writing.

Medical researchers and authors may improve their writing skills and avoid the same errors by consulting the list of retractions due to plagiarism which are tracked on the PubMed platform and discussed on the Retraction Watch blog.

Introduction

Plagiarism is one of the frequent forms of publication ethics violation. Researchers from all over the world may witness such a violation in their academic environment, and some of them may intentionally or unintentionally reuse their own or others’ intellectual property without proper processing and crediting [ 1 , 2 ].

Medical and allied health researchers are reminded that the Medical Subject Headings (MeSH) term defines plagiarism as “passing off as one’s own the work of another without credit” ( https://www.ncbi.nlm.nih.gov/mesh/?term=plagiarism ). This term was introduced back in 1990. Since then, global understanding of plagiarism has evolved to reflect a variety of unethical reuses of ideas, texts, and graphical materials [ 3 ].

The global open access movement has made it possible to easily reveal most instances of plagiarism, including copying texts and graphics across digitized old and new sources. The resultant retractions of erroneous and otherwise unethical articles have predominantly affected biomedical authors from China, India and Iran, particularly those who publish in low-impact journals [ 4 ]. The digitization of editorial management and regular scanning of countless online platforms have enabled detection of unethical reuse in manuscripts undergoing peer review [ 5 ]. Peer review digitization has also allowed exposure of instances of stealing ideas and materials which are intended for confidential and privileged evaluation by reviewers [ 6 ].

Intellectual theft is increasingly viewed as a serious ethical transgression in countries entering the global academic competition and adjusting their research and development policies to the universally acceptable norms. The awareness of various forms of plagiarism is growing due to the international research cooperation and quality publishing that involve academics with various language and cultural traditions. However, the issue of plagiarism in the globalized world of science is complicated due to variably perceived definitions of the unethical conduct, recycling of one’s own published materials, and unacceptable duplication of identical scientific information in different languages [ 7 ].

Editorial guidance on plagiarism

Global editorial recommendations contain a number of points instructing journal editors how to deal with suspected plagiarism and redundant/overlapping materials at pre- and post-publication stages. Core practices of the Committee on Publication Ethics (COPE) encourage editors to define plagiarism in their instructions and explicitly guide readers on how to reuse their published articles [ 8 ]. Also, all authors of manuscripts and published articles with misappropriation of intellectual property should be aware of their full responsibility for any wrongdoing at any stage. In case of suspicion, editors may question all co-authors and related authorities [ 9 ].

The Council of Science Editors (CSE) defines piracy and plagiarism as related violations of publication ethics with unauthorized reproduction of ideas, data, methods, and graphical materials, including those of the plagiarist (self-plagiarism and duplicate publication) [ 10 ]. Plagiarism, falsification, and fabrication are viewed by the CSE as different forms of research misconduct which may justify academic sanctions imposed by relevant national bodies and professional societies. To avoid any accusations of plagiarism, authors need to properly process primary literature and credit generators of ideas and other intellectual properties. Editors, in turn, should be skilled to identify copied and redundant materials by using advanced software and various other means.

Finally, the World Association of Medical Editors (WAME) reaffirms editorial intolerance of plagiarism in unpublished and published manuscripts and proposes to treat self-plagiarism differently, particularly in the case of linguistically redundant description of methods and other inevitable and unintentional duplications [ 11 ].

Creative thinking and plagiarism

Plagiarism is often revealed in works of novice non-Anglophone authors who are exposed to a conservative educational environment that encourages copying and memorizing and rejects creative thinking [ 12 , 13 ]. The gaps in training on research methodology, ethical writing, and acceptable editing support are also viewed as barriers to targeting influential journals by medical students and graduates [ 14 ].

The ease of accessing quality online articles of experienced authors, unawareness of plagiarism, and uncertain research ethics policies may push researchers in some academic institutions to copy, recycle, and produce unethical publications [ 15 , 16 ].

A large survey of Western and Eastern European Bachelor and Master degree students ( n = 1757) revealed diametrically opposite approaches to increasing awareness of plagiarism and arranging anti-plagiarism courses, with Polish students lacking training in these fields [ 17 ]. Additionally, a survey of 1100 undergraduate medical students in Pakistan pointed to a high percentage of unawareness of plagiarism (87%) and instances of plagiarism (71%) [ 18 ]. Finally, a nationwide survey of 706 Iranian medical graduates and faculty members revealed that the majority of the surveyees (74%) had not received any training on plagiarism [ 19 ]. The same survey revealed that 11% had not even heard about such an ethical transgression.

The existence of numerous editing and copying agencies preying on novice researchers, students, and authors may further complicate the issue and negatively affect scholarly publishing in China and some other non-Anglophone countries [ 9 ].

Instances of plagiarism

Several forms of plagiarism can be distinguished based on confounders of this misconduct ( Table I ). Depending on author intentions, plagiarism is classified into intentional and unintentional (accidental) forms [ 20 ]. The former is a deliberate unethical act aimed at misleading readers by skilled authors who steal ideas, texts, and graphics and present stolen materials as their own. Its detection is followed by academic sanctions and other punishments. The unintentional form may surface due to incorrectly paraphrasing and referencing previously published works [ 21 ].

Common instances of plagiarism

Inexperienced authors are often blamed for such misconduct, involving unattributed copying of text passages, scientific facts, and others’ ideas. Properly editing and referencing such manuscripts prior to journal submission and correcting erroneous articles by publishing apologies to readers could be sufficient in cases of unintentional plagiarism [ 22 ].

Experts distinguish plagiarism of ideas, words (texts), and images (graphics) [ 3 ]. Ideas can be stolen by unethical evaluators of grant projects, journal manuscripts, or other scholarly materials during the peer review, which is intentionally delayed to allow the plagiarist to publish his/her own article with misappropriated ideas first. Misappropriation of ideas and methodologies is a more serious and inconspicuous misconduct than copying of words [ 23 ].

Textual plagiarism manifests in various forms which can be detected by advanced search engines and software that analyze similarities across a sizeable amount of digitized publications. Direct, or word-for-word, and translational forms of plagiarism are relatively easy to detect by employing search engines and anti-plagiarism software [ 24 , 25 ]. Paraphrasing and patchwork plagiarism may confuse plagiarism detection systems by plagiarists’ attempts to replace a few words in the original text and misappropriate phrases and sentences. Careful manual checks and analyses of keywords and references may help to correctly interpret the similarity reports generated by software.

Plagiarists may intentionally increase the list of references by citing non-existent sources or incorrectly cite primary sources taken from secondary ones (systematic reviews) with the sole aim of misleading readers and concealing plagiarism of secondary publications [ 20 ]. A form of manipulation (“Trojan citation”) is also reported in connection with referring to relevant items to cover up substantive plagiarism and confuse journal editors and anti-plagiarism software [ 26 ].

Current anti-plagiarism software may detect unacknowledged recycled (self-plagiarized) texts, the so-called salami (data stemming from a single study spread across several papers) and augmented (opposite to salami) texts. Accusations of plagiarism in such cases require thorough manual checks of all similar parts, particularly by experts in the professional field.

Detecting identical abstracts requires special consideration due to the similarities of some full texts with congress abstracts and preprints, which are unpublished items and do not account for plagiarism. As such, authors should be advised to provide notes in their manuscripts, linking to previously posted congress abstracts and reposted preprints.

While concentrating on textual similarities, editors employing anti-plagiarism software often overlook graphical overlaps which may reveal compound forms of ethics violation and copyright infringement [ 27 , 28 ]. Thorough graphical analyses are particularly required for manuscripts with tables, figures, depiction of technological processes, and chemical formulae [ 29 ]. Questioning authors about the authenticity of all materials, requesting official reuse permissions from copyright holders, and referencing primary sources of reused or modified graphics may help to avoid unethical conduct and copyright infringement [ 30 ].

With the advent of anti-plagiarism software, some journal editors set limits of minor, moderate, and unacceptable copying and text recycling. They argue that less than 10% of verbatim copying, particularly in Methods section, could be tolerated provided there are no linguistic options to paraphrase [ 31 ]. Accordingly, 15–20% of textual overlap is judged as less tolerable and more than 30% as unacceptable. Although such a quantitative classification helps stratify anti-plagiarism measures, most experts advocate a zero tolerance policy since even a small percentage of copying may reveal complicated and concealed ethics violations [ 32 ].

Plagiarism detection

Researchers should be aware of what constitutes plagiarism and how to detect it ( Table II ). Those authors who master academic English, familiarize themselves with bibliographic searches, and advance their graphics designing skills may avoid most instances of plagiarism, duplication, and copyright infringement. Those who employ anti-plagiarism tools should combine software and human-detection options.

Strategies for plagiarism detection

Although none of the currently available anti-plagiarism systems is perfect [ 33 ], overlooking the importance of related editorial checks may affect the authenticity of scholarly publications and lead to the so-called predatory practices [ 34 , 35 ]. Generally, employing popular online platforms such as Google Scholar, Grammarly, and PlagScan makes it possible to improve the quality of references, readability, and linguistic style of scholarly manuscripts and increase their likelihood of acceptance by influential journals [ 36 ]. The role of processing manuscripts through freely available plagiarism detection tools is difficult to overestimate, since most researchers and faculty members, particularly in developing countries, lack access to proprietary software [ 37 ].

Preliminary evidence suggests that there are differences in the prevalence of textual plagiarism across academic disciplines, necessitating careful checks in science, technology, engineering, and mathematics journal submissions [ 38 ]. Additionally, in the era of digitization and open access, reviews are more likely to contain “copy-and-paste” written sections, pointing to the particular need for checks of this type of article [ 39 ].

Plagiarism detection and verification is largely based on text-matching search engines and computer software that report similarity scores. The advanced software is integrated with numerous publishers and online platforms to allow scanning of potential overlaps among countless open-access and subscription literature items [ 40 ]. Perhaps the most advanced anti-plagiarism system is iThenticate, which is employed by most established publishers to report the overall similarity score and similarity score from a single source [ 41 ]. The system offers options to filter direct quotations, bibliographies, and methodologies to minimize chances of erroneous reports [ 42 ]. High overall similarity scores (>35%) often point to plagiarism requiring outright rejection or retraction [ 43 ].

Regular iThenticate checks have made it possible to minimize, but not exclude, unethical publications [ 44 ]. The reported similarity scores should not replace editorial decisions and should be accompanied by careful reading and validation of references [ 45 ].

Compared to textual similarity detection, image plagiarism detection is a more challenging task, since it often requires both image processing and semantic mapping techniques [ 46 , 47 ]. Google Images is a widely available search engine that can be used to reveal identical or manipulated images processed by Google [ 48 ]. However, this engine fails to detect copied and modified graphical materials. Semantic analyses are particularly useful in such a scenario of image modification. In fact, processing image legends through textual similarity tests may point to misconduct with modified images.

Attempts are underway to propose an advanced system for tracking plagiarism of graphics [ 49 ]. In the meantime, journal editors with a special interest in publishing graphics need to instruct their authors on what constitutes image plagiarism and how to ethically reuse related contents [ 50 ].

Retractions due to plagiarism

Although retractions of published articles are generally not frequent, their analyses may reveal country- and discipline-related differences in editorial strategies, misconduct prevention policies, and enforced measures [ 51 , 52 ]. Examining details of retracted articles which are publicly discussed on the Retraction Watch blog may also prioritize ethics topics for postgraduate education [ 53 , 54 ].

With the widespread use of iThenticate and other plagiarism detection software, numerous related retractions have taken place over the past decade. When retraction notices in PubMed are compared, similar percentages of plagiarism (about 20%) were mentioned in 2008 and 2016 samples [ 55 ]. The number of retractions due to plagiarism varies across countries and academic disciplines, with the U.S., China, Germany, Japan and the U.K. accounting for 3 out of 4 retractions in a sample of 130 surgery articles [ 51 ]. The same study estimated a plagiarism rate of 16% in these articles. Also, an analysis of 176 retractions in obstetrics and gynecology indicated 40 cases of plagiarism (23%) [ 56 ]. In rehabilitation and sport sciences, retractions due to plagiarism were reported in 11 (26%) and 7 (13%) cases, respectively [ 57 ]. And finally, an analysis of 22 rheumatology retractions revealed 7 (32%) cases of plagiarism in review articles [ 58 ].

Conclusions

Plagiarism continues to affect the integrity of scholarly publications worldwide. Digitization and open access provide numerous opportunities for accessing and disseminating scientific information. However, some researchers and authors are tempted to intentionally or unintentionally embark on shortcuts and construct their articles with copied and unattributed texts, graphics, and ideas. Arguably, educating authors how to systematically access and process literature and how to master academic English may prevent most instances of modern-day plagiarism. Systematic searches are necessary for choosing new topics and avoiding redundancies. Processing retrieved articles, appropriately referring to published scientific facts, and writing in one’s own words may further improve the ethical standing of new manuscripts.

Researchers and research managers alike need to learn more about globally acceptable writing practices, regularly analyze retractions due to plagiarism, and avoid related errors in their practice. Knowledge of global editorial guidance and plagiarism detection and prevention strategies is essential for successful writing and targeting influential ethical journals. Journal editors should enforce a “trust, but verify” policy by performing plagiarism checks, inquiring about authors’ writing practices, and asking for disclaimers if suspicion of plagiarism persists.

The authors declare no conflict of interest.

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Academic Plagiarism Detection

• First Online: 01 August 2023

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• Norman Meuschke 2  

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This chapter provides background information on academic plagiarism and reviews technical approaches to detect it. Section Chapter 1 derives a definition and typology of academic plagiarism that is suitable for the technical research focus of this thesis. Section 2.2 provides a holistic overview of the research on academic plagiarism to contextualize the technically focused research areas that the subsequent sections present in detail. Sections 2.3 and 2.4 systematically analyze the research on plagiarism detection methods and describe production-grade systems that implement some of the presented methods. Section 2.5 presents datasets usable for evaluating plagiarism detection technology. Furthermore, the section discusses comprehensive performance evaluations of plagiarism detection methods and systems to highlight their weaknesses and demonstrate the research gap this thesis addresses. Section 2.6 summarizes the findings of the literature review and thereby fulfills Research Task 1. Section 2.7 derives the research idea pursued in this thesis.

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PAN is a series of annual competitions for evaluating PD technology (see Section 2.5.1, p. 49).

Turnitin, a major provider of plagiarism detection software, states that 15,000 institutions in 150 countries use its service [510]

Parallel corpora consist of texts in language A and the translations of the texts in language B. Comparable corpora consist of texts of the same type, e.g., news articles, or on the same topic written in different languages. The text are not translations of one another [269, p. 487].

We use other identifiers than Potthast et al. to be consistent with other formulae in this thesis.

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Meuschke, N. (2023). Academic Plagiarism Detection. In: Analyzing Non-Textual Content Elements to Detect Academic Plagiarism. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-42062-8_2

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