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41.
Debasis?GangulyEmail authorView authors OrcID profile Gareth?J.?F.?Jones Aarón?Ramírez-de-la-Cruz Gabriela?Ramírez-de-la-Rosa Esaú?Villatoro-Tello 《Information Retrieval》2018,21(1):1-23
Automatic detection of source code plagiarism is an important research field for both the commercial software industry and within the research community. Existing methods of plagiarism detection primarily involve exhaustive pairwise document comparison, which does not scale well for large software collections. To achieve scalability, we approach the problem from an information retrieval (IR) perspective. We retrieve a ranked list of candidate documents in response to a pseudo-query representation constructed from each source code document in the collection. The challenge in source code document retrieval is that the standard bag-of-words (BoW) representation model for such documents is likely to result in many false positives being retrieved, because of the use of identical programming language specific constructs and keywords. To address this problem, we make use of an abstract syntax tree (AST) representation of the source code documents. While the IR approach is efficient, it is essentially unsupervised in nature. To further improve its effectiveness, we apply a supervised classifier (pre-trained with features extracted from sample plagiarized source code pairs) on the top ranked retrieved documents. We report experiments on the SOCO-2014 dataset comprising 12K Java source files with almost 1M lines of code. Our experiments confirm that the AST based approach produces significantly better retrieval effectiveness than a standard BoW representation, i.e., the AST based approach is able to identify a higher number of plagiarized source code documents at top ranks in response to a query source code document. The supervised classifier, trained on features extracted from sample plagiarized source code pairs, is shown to effectively filter and thus further improve the ranked list of retrieved candidate plagiarized documents. 相似文献
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ABSTRACTEmploying a number of different standalone programs is a prevalent approach among communication scholars who use computational methods to analyze media content. For instance, a researcher might use a specific program or a paid service to scrape some content from the Web, then use another program to process the resulting data, and finally conduct statistical analysis or produce some visualizations in yet another program. This makes it hard to build reproducible workflows, and even harder to build on the work of earlier studies. To improve this situation, we propose and discuss four criteria that a framework for automated content analysis should fulfill: scalability, free and open source, adaptability, and accessibility via multiple interfaces. We also describe how to put these considerations into practice, discuss their feasibility, and point toward future developments. 相似文献
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Joseph Deodato 《Journal of Web Librarianship》2018,12(1):1-27
The emergence of social media has radically transformed the way we create and consume information. These changes have in turn given rise to new models of librarianship centered on principles of participation, interaction, and collaboration. Over the last decade, academic libraries have eagerly adopted social media as a means of enhancing services and connecting with a new generation of users. But how exactly has this technology changed libraries? In what ways has the social web transformed library services or our relationships with users? This article attempts to assess the impact of social media on academic libraries in the United States through a review of the literature published since 2005. In particular, it looks at how academic libraries have used social media to improve or develop new services. By comparing published case studies with the theoretical literature, this article seeks to separate theory from practice and determine the extent to which the social web has transformed library practice. The author concludes that, despite several noteworthy examples, the majority of social library applications ultimately fail to live up to the transformative potential promised within the literature and that this failure may have more to do with philosophical rather than technical limitations. 相似文献
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Mario Mali
ki Joseph Costello Juan Pablo Alperin Lauren A. Maggio 《Biochemia medica : ?asopis Hrvatskoga dru?tva medicinskih biokemi?ara / HDMB》2021,31(2)
IntroductionWhile early commenting on studies is seen as one of the advantages of preprints, the type of such comments, and the people who post them, have not been systematically explored.Materials and methodsWe analysed comments posted between 21 May 2015 and 9 September 2019 for 1983 bioRxiv preprints that received only one comment on the bioRxiv website. The comment types were classified by three coders independently, with all differences resolved by consensus.ResultsOur analysis showed that 69% of comments were posted by non-authors (N = 1366), and 31% by the preprints’ authors themselves (N = 617). Twelve percent of non-author comments (N = 168) were full review reports traditionally found during journal review, while the rest most commonly contained praises (N = 577, 42%), suggestions (N = 399, 29%), or criticisms (N = 226, 17%). Authors’ comments most commonly contained publication status updates (N = 354, 57%), additional study information (N = 158, 26%), or solicited feedback for the preprints (N = 65, 11%).ConclusionsOur results indicate that comments posted for bioRxiv preprints may have potential benefits for both the public and the scholarly community. Further research is needed to measure the direct impact of these comments on comments made by journal peer reviewers, subsequent preprint versions or journal publications. 相似文献
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