Overview of the PAN'2016 - New Challenges for Authorship Analysis: Cross-genre Profiling, Clustering, Diarization, and Obfuscation

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-44564-9_28This paper presents an overview of the PAN/CLEF evaluation lab. During the last decade, PAN has been established as the main forum of digital text forensic research. PAN 2016 comprises three shared tasks: (i) author identification, addressing author clustering and diarization (or intrinsic plagiarism detection); (ii) author profiling, addressing age and gender prediction from a cross-genre perspective; and (iii) author obfuscation, addressing author masking and obfuscation evaluation. In total, 35 teams participated in all three shared tasks of PAN 2016 and, following the practice of previous editions, software submissions were required and evaluated within the TIRA experimentation framework.The work of the first author was partially supported by the Som EMBED TIN2015-71147-C2-1-P MINECO research project and by the Generalitat Valenciana under the grant ALMA MATER (Prometeo II/2014/030). The work of the second author was partially supported by Autoritas Consulting and by Ministerio de Economía y Competitividad de España under grant ECOPORTUNITY IPT-2012-1220-430000.Rosso, P.; Rangel-Pardo, FM.; Potthast, M.; Stamatatos, E.; Tschuggnall, M.; Stein, B. (2016). Overview of the PAN'2016 - New Challenges for Authorship Analysis: Cross-genre Profiling, Clustering, Diarization, and Obfuscation. En Experimental IR Meets Multilinguality, Multimodality, and Interaction. Springer Verlag (Germany). 332-350. https://doi.org/10.1007/978-3-319-44564-9_28S332350Almishari, M., Tsudik, G.: Exploring linkability of user reviews. In: Foresti, S., Yung, M., Martinelli, F. (eds.) ESORICS 2012. LNCS, vol. 7459, pp. 307–324. Springer, Heidelberg (2012)Álvarez-Carmona, M.A., López-Monroy, A.P., Montes-Y-Gómez, M., Villaseñor-Pineda, L., Jair-Escalante, H.: INAOE’s Participation at PAN’15: author profiling task–notebook for PAN at CLEF 2015. 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Plagiarism meets paraphrasing: insights for the new generation in automatic plagiarism detection

Although paraphrasing is the linguistic mechanism underlying many plagiarism cases, little attention has been paid to its analysis in the framework of automatic plagiarism detection. Therefore, state-of-the-art plagiarism detectors find it difficult to detect cases of paraphrase plagiarism. In this article, we analyse the relationship between paraphrasing and plagiarism, paying special attention to which paraphrase phenomena underlie acts of plagiarism and which of them are detected by plagiarism detection systems. With this aim in mind, we created the P4P corpus, a new resource which uses a paraphrase typology to annotate a subset of the PAN-PC-10 corpus for automatic plagiarism detection. The results of the Second International Competition on Plagiarism Detection were analysed in the light of this annotation. The presented experiments show that (i) more complex paraphrase phenomena and a high density of paraphrase mechanisms make plagiarism detection more difficult, (ii) lexical substitutions are the paraphrase mechanisms used the most when plagiarising, and (iii) paraphrase mechanisms tend to shorten the plagiarized text. For the first time, the paraphrase mechanisms behind plagiarism have been analysed, providing critical insights for the improvement of automatic plagiarism detection systems

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