Integrating syntax‐semantic‐based text analysis with structural and citation information for scientific plagiarism detection

Vani, K.; Gupta, Deepa

doi:10.1002/asi.24027

Cited by 10 publications

(3 citation statements)

References 39 publications

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“…In the library and information science (LIS) literature, text analysis has been used to analyze LIS job postings (Durr, 2020;Maceli, 2015); plagiarism software detection (Vani & Gupta, 2018); classification methodologies (Moohebat et al, 2015); faculty publication trends (Gao, 2017); and ebook usage (Bakkalbasi & Goertzen, 2015).…”

Section: Text Analysis and Assessing Il Via Acrlmentioning

confidence: 99%

A Text Analysis of Four Levels of Librarian Involvement and Impact on Students in an Inquiry-Based Learning Course

Stoeckle

Murphy²,

Lenart³

2022

Partnership

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Librarians at the University of Calgary collaborated with instructors on an inquiry-based learning course with varying involvement across four course sections. This study uses text analysis of student assignments to assess information literacy (IL) skill development across four levels of course participation: librarian as instructor-of-record, two levels of embeddedness, and a single ‘one-shot’ session. The methodology included the tracking of keywords generated using the ACRL Framework for Information Literacy and text analysis of student reflection assignments in an inquiry-based, research-focused first-year undergraduate course. The results suggest that the benefit to student IL skills is not related to amount of librarian instruction, but rather to the level of instructor buy-in with regard to library services and the importance of IL skills. We argue that the most impactful librarian involvement is as an IL course consultant rather than a full-time embedded librarian (which is surprising given the literature on the efficacy of embeddedness). Although further research is needed, the study results have significant implications for academic librarian instructional practices and collaborations on course content with faculty members.

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Section: Text Analysis and Assessing Il Via Acrlmentioning

confidence: 99%

A Text Analysis of Four Levels of Librarian Involvement and Impact on Students in an Inquiry-Based Learning Course

Stoeckle

Murphy²,

Lenart³

2022

Partnership

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“…Detailed analysis plays a key role in the performance of CLPD. In previous literature of CLPD, two main streams of methods have been proposed: citation‐based approach and content‐based approach (Vani & Gupta, 2018). Though the citation information is language‐independent, Pertile, Moreira, and Rosso (2016) compare the performance of the citation‐based approach and the content‐based approach, and report the inferior performance of citation‐based approach.…”

Section: Introductionmentioning

confidence: 99%

Employing word mover's distance for cross‐lingual plagiarized text detection

Chang

Hwang

2020

Proc Assoc Inf Sci Technol

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While the blossom of globalization has achieved many successes, cross‐lingual plagiarism, however, has become popular. Detecting plagiarism across languages requires the capability of comparing semantical similarities between texts of different languages. Previous works rely on massive bilingual resources such as comparable corpus, parallel corpus, and even commercial machine translation as references. However, towards domain‐specific applications, collecting such resources is labor‐intensive and impractical. Also, the absence of interpretability of existing methods lead to the difficulty of investigating retrieval results by humans. Hence, it is imperative to have a resource‐light and interpretable method for cross‐lingual plagiarism detection. In this study, we propose a new detection method, called CL‐WMD, which is built upon word embedding techniques. CL‐WMD requires only a small set of translation pairs to constitute a bilingual reference and calculates semantical distances between texts by word mover's distance, which can provide explicable word alignment information between two compared text spans. Our experiments are conducted under a bilingual scientific publication corpus composed of two typologically diverse languages: English and Chinese. The results demonstrate that CL‐WMD has higher accuracy than most existing methods and achieves better or comparable performance when compared to the translation‐based method in paragraph‐level and sentence‐level plagiarism detection tasks.

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“…A common approach is plagiarism detection which is mainly to determine whether the media has copied or plagiarized content. Paper [3] proposes that texts are segmented and then tested. And plagiarism detection in text using the vector space model [4].…”

Section: Introductionmentioning

confidence: 99%

DCDChain: A Credible Architecture of Digital Copyright Detection Based on Blockchain

Chen

Wang²,

Ni³

et al. 2020

Preprint

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Copyright detection is an effective method to prevent piracy. However, untrustworthy detection parties may lead to falsified detection results. Due to its credibility and tamper resistance, blockchain has been applied to copyright protection. Previous works mainly utilized blockchain for reliable copyright information storage or copyrighted digital media trading. As far as we know, the problem of credible copyright detection has not been addressed. In this paper, we propose a credible copyright detection architecture based on the blockchain, called DCDChain. In this architecture, the detection agency first detects copyrights off the chain, then uploads the detection records to the blockchain. Since data on the blockchain are publicly accessible, media providers can verify the correctness of the copyright detection, and appeal to a smart contract if there is any dissent. The smart contract then arbitrates the disputes by verifying the correctness of detection on the chain. The detect-verify-and-arbitrate mechanism guarantees the credibility of copyright detection. Privacy and security analysis and experimental simulations show that the digital copyright detection architecture is reliable, secure and efficient.

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Integrating syntax‐semantic‐based text analysis with structural and citation information for scientific plagiarism detection

Cited by 10 publications

References 39 publications

A Text Analysis of Four Levels of Librarian Involvement and Impact on Students in an Inquiry-Based Learning Course

A Text Analysis of Four Levels of Librarian Involvement and Impact on Students in an Inquiry-Based Learning Course

Employing word mover's distance for cross‐lingual plagiarized text detection

DCDChain: A Credible Architecture of Digital Copyright Detection Based on Blockchain

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