Climate Dynamics: A Network-Based Approach for the Analysis of Global Precipitation

Precipitation is one of the most important meteorological variables for defining the climate dynamics, but the spatial patterns of precipitation have not been fully investigated yet. The complex network theory, which provides a robust tool to investigate the statistical interdependence of many interacting elements, is used here to analyze the spatial dynamics of annual precipitation over seventy years (1941-2010). The precipitation network is built associating a node to a geographical region, which has a temporal distribution of precipitation, and identifying possible links among nodes through the correlation function. The precipitation network reveals significant spatial variability with barely connected regions, as Eastern China and Japan, and highly connected regions, such as the African Sahel, Eastern Australia and, to a lesser extent, Northern Europe. Sahel and Eastern Australia are remarkably dry regions, where low amounts of rainfall are uniformly distributed on continental scales and small-scale extreme events are rare. As a consequence, the precipitation gradient is low, making these regions well connected on a large spatial scale. On the contrary, the Asiatic South-East is often reached by extreme events such as monsoons, tropical cyclones and heat waves, which can all contribute to reduce the correlation to the short-range scale only. Some patterns emerging between mid-latitude and tropical regions suggest a possible impact of the propagation of planetary waves on precipitation at a global scale. Other links can be qualitatively associated to the atmospheric and oceanic circulation. To analyze the sensitivity of the network to the physical closeness of the nodes, short-term connections are broken. The African Sahel, Eastern Australia and Northern Europe regions again appear as the supernodes of the network, confirming furthermore their long-range connection structure. Almost all North-American and Asian nodes vanish, revealing that extreme events can enhance high precipitation gradients, leading to a systematic absence of long-range patterns

Overview of PAN'17: Author Identification, Author Profiling, and Author Obfuscation

[EN] The PAN 2017 shared tasks on digital text forensics were held in conjunction with the annual CLEF conference. This paper gives a high-level overview of each of the three shared tasks organized this year, namely author identification, author profiling, and author obfuscation. For each task, we give a brief summary of the evaluation data, performance measures, and results obtained. Altogether, 29 participants submitted a total of 33 pieces of software for evaluation, whereas 4 participants submitted to more than one task. All submitted software has been deployed to the TIRA evaluation platform, where it remains hosted for reproducibility purposes.The work at the Universitat Politècnica de València was funded by the MINECO research project SomEMBED (TIN2015-71147-C2-1-P).Potthast, M.; Rangel-Pardo, FM.; Tschuggnall, M.; Stamatatos, E.; Rosso, P.; Stein, B. (2017). Overview of PAN'17: Author Identification, Author Profiling, and Author Obfuscation. Lecture Notes in Computer Science. 10456:275-290. https://doi.org/10.1007/978-3-319-65813-1_25S27529010456Amigó, E., Gonzalo, J., Artiles, J., Verdejo, F.: A comparison of extrinsic clustering evaluation metrics based on formal constraints. Inf. Retrieval 12(4), 461–486 (2009)Bagnall, D.: Authorship clustering using multi-headed recurrent neural networks—notebook for PAN at CLEF 2016. In: Balog et al. [3] (2016). http://ceur-ws.org/Vol-1609/Balog, K., Cappellato, L., Ferro, N., Macdonald, C. (eds.): CLEF 2016 Evaluation Labs and Workshop – Working Notes Papers, 5–8 September, Évora, Portugal. CEUR Workshop Proceedings. CEUR-WS.org (2016). http://www.clef-initiative.eu/publication/working-notesClarke, C.L., Craswell, N., Soboroff, I., Voorhees, E.M.: Overview of the TREC 2009 web track. Technical report, DTIC Document (2009)García, Y., Castro, D., Lavielle, V., Noz, R.M.: Discovering author groups using a $$\beta$$ β -compact graph-based clustering. In: Cappellato, L., Ferro, N., Goeuriot, L., Mandl, T. (eds.) CLEF 2017 Working Notes. CEUR Workshop Proceedings, CLEF and CEUR-WS.org, September 2017Glavaš, G., Nanni, F., Ponzetto, S.P.: Unsupervised text segmentation using semantic relatedness graphs. In: Association for Computational Linguistics (2016)Gollub, T., Stein, B., Burrows, S.: Ousting ivory tower research: towards a web framework for providing experiments as a service. In: Hersh, B., Callan, J., Maarek, Y., Sanderson, M. (eds.) 35th International ACM Conference on Research and Development in Information Retrieval (SIGIR 2012), pp. 1125–1126. ACM, August 2012Gómez-Adorno, H., Aleman, Y., no, D.V., Sanchez-Perez, M.A., Pinto, D., Sidorov, G.: Author clustering using hierarchical clustering analysis. In: Cappellato, L., Ferro, N., Goeuriot, L., Mandl, T. (eds.) CLEF 2017 Working Notes. CEUR Workshop Proceedings, CLEF and CEUR-WS.org, September 2017Hagen, M., Potthast, M., Stein, B.: Overview of the author obfuscation task at PAN 2017: safety evaluation revisited. In: Cappellato, L., Ferro, N., Goeuriot, L., Mandl, T. (eds.) Working Notes Papers of the CLEF 2017 Evaluation Labs. CEUR Workshop Proceedings, CLEF and CEUR-WS.org, September 2017Halvani, O., Graner, L.: Author clustering based on compression-based dissimilarity scores. In: Cappellato, L., Ferro, N., Goeuriot, L., Mandl, T. (eds.) CLEF 2017 Working Notes. CEUR Workshop Proceedings, CLEF and CEUR-WS.org, September 2017Hearst, M.A.: TextTiling: segmenting text into multi-paragraph subtopic passages. Comput. Linguist. 23(1), 33–64 (1997)Kiros, R., Zhu, Y., Salakhutdinov, R.R., Zemel, R., Urtasun, R., Torralba, A., Fidler, S.: Skip-thought vectors. In: Advances in Neural Information Processing Systems (NIPS), pp. 3294–3302 (2015)Kocher, M., Savoy, J.: UniNE at CLEF 2017: author clustering. In: Cappellato, L., Ferro, N., Goeuriot, L., Mandl, T. (eds.) CLEF 2017 Working Notes. CEUR Workshop Proceedings, CLEF and CEUR-WS.org, September 2017Koppel, M., Akiva, N., Dershowitz, I., Dershowitz, N.: Unsupervised decomposition of a document into authorial components. In: Lin, D., Matsumoto, Y., Mihalcea, R. (eds.) Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics (ACL), pp. 1356–1364 (2011)Misra, H., Yvon, F., Jose, J.M., Cappe, O.: Text segmentation via topic modeling: an analytical study. In: Proceedings of CIKM 2009, pp. 1553–1556. ACM (2009)Pevzner, L., Hearst, M.A.: A critique and improvement of an evaluation metric for text segmentation. Comput. Linguis. 28(1), 19–36 (2002)Potthast, M., Eiselt, A., Barrón-Cedeño, A., Stein, B., Rosso, P.: Overview of the 3rd international competition on plagiarism detection. In: Notebook Papers of the 5th Evaluation Lab on Uncovering Plagiarism, Authorship and Social Software Misuse (PAN), Amsterdam, The Netherlands, September 2011Potthast, M., Gollub, T., Rangel, F., Rosso, P., Stamatatos, E., Stein, B.: Improving the reproducibility of PAN’s shared tasks: plagiarism detection, author identification, and author profiling. In: Kanoulas, E., Lupu, M., Clough, P., Sanderson, M., Hall, M., Hanbury, A., Toms, E. (eds.) CLEF 2014. LNCS, vol. 8685, pp. 268–299. Springer, Cham (2014). doi: 10.1007/978-3-319-11382-1_22Potthast, M., Hagen, M., Stein, B.: Author obfuscation: attacking the state of the art in authorship verification. In: Working Notes Papers of the CLEF 2016 Evaluation Labs. CEUR Workshop Proceedings, CLEF and CEUR-WS.org, September 2016. http://ceur-ws.org/Vol-1609/Potthast, M., Hagen, M., Völske, M., Stein, B.: Crowdsourcing interaction logs to understand text reuse from the web. In: Fung, P., Poesio, M. (eds.) Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 13), pp. 1212–1221. Association for Computational Linguistics (2013). http://www.aclweb.org/anthology/p13-1119Rangel, F., Celli, F., Rosso, P., Potthast, M., Stein, B., Daelemans, W.: Overview of the 3rd author profiling task at PAN 2015. In: Cappellato, L., Ferro, N., Jones, G., San Juan, E. (eds.) CLEF 2015 Evaluation Labs and Workshop – Working Notes Papers, 8–11 September, Toulouse, France. CEUR Workshop Proceedings, CEUR-WS.org, September 2015Rangel, F., Rosso, P., Chugur, I., Potthast, M., Trenkmann, M., Stein, B., Verhoeven, B., Daelemans, W.: Overview of the 2nd author profiling task at PAN 2014. In: Cappellato, L., Ferro, N., Halvey, M., Kraaij, W. (eds.) CLEF 2014 Evaluation Labs and Workshop – Working Notes Papers, 15–18 September, Sheffield, UK. CEUR Workshop Proceedings, CEUR-WS.org, September 2014Rangel, F., Rosso, P., Franco-Salvador, M.: A low dimensionality representation for language variety identification. In: 17th International Conference on Intelligent Text Processing and Computational Linguistics, CICLing. LNCS. Springer (2016). arXiv:1705.10754Rangel, F., Rosso, P., Koppel, M., Stamatatos, E., Inches, G.: Overview of the author profiling task at PAN 2013. In: Forner, P., Navigli, R., Tufis, D. (eds.) CLEF 2013 Evaluation Labs and Workshop – Working Notes Papers, 23–26 September, Valencia, Spain (2013)Rangel, F., Rosso, P., Potthast, M., Stein, B.: Overview of the 5th author profiling task at PAN 2017: gender and language variety identification in Twitter. In: Cappellato, L., Ferro, N., Goeuriot, L., Mandl, T. (eds.) Working Notes Papers of the CLEF 2017 Evaluation Labs. CEUR Workshop Proceedings, CLEF and CEUR-WS.org, September 2017Rangel, F., Rosso, P., Verhoeven, B., Daelemans, W., Potthast, M., Stein, B.: Overview of the 4th author profiling task at PAN 2016: cross-genre evaluations. In: Balog et al. [3]Riedl, M., Biemann, C.: TopicTiling: a text segmentation algorithm based on LDA. In: Proceedings of ACL 2012 Student Research Workshop, pp. 37–42. Association for Computational Linguistics (2012)Scaiano, M., Inkpen, D.: Getting more from segmentation evaluation. In: Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. pp. 362–366. Association for Computational Linguistics (2012)Stamatatos, E., Tschuggnall, M., Verhoeven, B., Daelemans, W., Specht, G., Stein, B., Potthast, M.: Clustering by authorship within and across documents. In: Working Notes Papers of the CLEF 2016 Evaluation Labs. CEUR Workshop Proceedings, CLEF and CEUR-WS.org. http://ceur-ws.org/Vol-1609/Stamatatos, E., Tschuggnall, M., Verhoeven, B., Daelemans, W., Specht, G., Stein, B., Potthast, M.: Clustering by authorship within and across documents. In: Working Notes Papers of the CLEF 2016 Evaluation Labs. CEUR Workshop Proceedings, CLEF and CEUR-WS.org, September 2016Tschuggnall, M., Stamatatos, E., Verhoeven, B., Daelemans, W., Specht, G., Stein, B., Potthast, M.: Overview of the author identification task at PAN-2017: style breach detection and author clustering. In: Cappellato, L., Ferro, N., Goeuriot, L., Mandl, T. (eds.) Working Notes Papers of the CLEF 2017 Evaluation Labs. CEUR Workshop Proceedings, CLEF and CEUR-WS.org, September 201

Parallel particle swarm optimization based on spark for academic paper co-authorship prediction

The particle swarm optimization (PSO) algorithm has been widely used in various optimization problems. Although PSO has been successful in many fields, solving optimization problems in big data applications often requires processing of massive amounts of data, which cannot be handled by traditional PSO on a single machine. There have been several parallel PSO based on Spark, however they are almost proposed for solving numerical optimization problems, and few for big data optimization problems. In this paper, we propose a new Spark-based parallel PSO algorithm to predict the co-authorship of academic papers, which we formulate as an optimization problem from massive academic data. Experimental results show that the proposed parallel PSO can achieve good prediction accuracy

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. In: Working Notes Papers of the CLEF 2015 Evaluation Labs. CEUR-WS.org, vol. 1391 (2015)Amigó, E., Gonzalo, J., Artiles, J., Verdejo, F.: A comparison of extrinsic clustering evaluation metrics based on formal constraints. Inf. Retrieval 12(4), 461–486 (2009)Argamon, S., Juola, P.: Overview of the international authorship identification competition at PAN-2011. In: Working Notes Papers of the CLEF 2011 Evaluation Labs (2011)Argamon, S., Koppel, M., Fine, J., Shimoni, A.R.: Gender, genre, and writing style in formal written texts. TEXT 23, 321–346 (2003)Bagnall, D.: Author identification using multi-headed recurrent neural networks. In: Working Notes Papers of the CLEF 2015 Evaluation Labs. CEUR-WS.org, vol. 1391 (2015)Bensalem, I., Boukhalfa, I., Rosso, P., Abouenour, L., Darwish, K., Chikhi, S.: Overview of the AraPlagDet PAN@ FIRE2015 shared task on arabic plagiarism detection. In: Notebook Papers of FIRE 2015. CEUR-WS.org, vol. 1587 (2015)Burger, J.D., Henderson, J., Kim, G., Zarrella, G.: Discriminating gender on twitter. In: Proceedings of EMNLP 2011 (2011)Burrows, S., Potthast, M., Stein, B.: Paraphrase acquisition via crowdsourcing and machine learning. ACM TIST 4(3), 43:1–43:21 (2013)Castillo, E., Cervantes, O., Vilariño, D., Pinto, D., León, S.: Unsupervised method for the authorship identification task. In: CLEF 2014 Labs and Workshops, Notebook Papers. CEUR-WS.org, vol. 1180 (2014)Chaski, C.E.: Who’s at the keyboard: authorship attribution in digital evidence invesigations. Int. J. Digit. Evid. 4, 1–13 (2005)Clarke, C.L., Craswell, N., Soboroff, I., Voorhees, E.M.: Overview of the TREC 2009 web track. In: DTIC Document (2009)Flores, E., Rosso, P., Moreno, L., Villatoro, E.: On the detection of source code re-use. In: ACM FIRE 2014 Post Proceedings of the Forum for Information Retrieval Evaluation, pp. 21–30 (2015)Flores, E., Rosso, P., Villatoro, E., Moreno, L., Alcover, R., Chirivella, V.: PAN@FIRE: overview of CL-SOCO track on the detection of cross-language source code re-use. In: Notebook Papers of FIRE 2015. CEUR-WS.org, vol. 1587 (2015)Fréry, J., Largeron, C., Juganaru-Mathieu, M.: UJM at clef in author identification. In: CLEF 2014 Labs and Workshops, Notebook Papers. CEUR-WS.org, vol. 1180 (2014)Gollub, T., Potthast, M., Beyer, A., Busse, M., Rangel, F., Rosso, P., Stamatatos, E., Stein, B.: Recent trends in digital text forensics and its evaluation. In: Forner, P., Müller, H., Paredes, R., Rosso, P., Stein, B. (eds.) CLEF 2013. LNCS, vol. 8138, pp. 282–302. Springer, Heidelberg (2013)Gollub, T., Stein, B., Burrows, S.: Ousting Ivory tower research: towards a web framework for providing experiments as a service. In: Proceedings of SIGIR 12. ACM (2012)Hagen, M., Potthast, M., Stein, B.: Source retrieval for plagiarism detection from large web corpora: recent approaches. In: Working Notes Papers of the CLEF 2015 Evaluation Labs. CEUR-WS.org, vol. 1391 (2015)van Halteren, H.: Linguistic profiling for author recognition and verification. In: Proceedings of ACL 2004 (2004)Holmes, J., Meyerhoff, M.: The Handbook of Language and Gender. Blackwell Handbooks in Linguistics, Wiley (2003)Iqbal, F., Binsalleeh, H., Fung, B.C.M., Debbabi, M.: Mining writeprints from anonymous e-mails for forensic investigation. Digit. Investig. 7(1–2), 56–64 (2010)Jankowska, M., Keselj, V., Milios, E.: CNG text classification for authorship profiling task-notebook for PAN at CLEF 2013. In: Working Notes Papers of the CLEF 2013 Evaluation Labs. CEUR-WS.org, vol. 1179 (2013)Juola, P.: An overview of the traditional authorship attribution subtask. In: Working Notes Papers of the CLEF 2012 Evaluation Labs (2012)Juola, P.: Authorship attribution. Found. Trends Inf. Retrieval 1, 234–334 (2008)Juola, P.: How a computer program helped reveal J.K. rowling as author of a Cuckoo’s calling. In: Scientific American (2013)Juola, P., Stamatatos, E.: Overview of the author identification task at PAN-2013. In:Working Notes Papers of the CLEF 2013 Evaluation Labs. CEUR-WS.org vol. 1179 (2013)Keswani, Y., Trivedi, H., Mehta, P., Majumder, P.: Author masking through translation-notebook for PAN at CLEF 2016. In: Conference and Labs of the Evaluation Forum, CLEF (2016)Koppel, M., Argamon, S., Shimoni, A.R.: Automatically categorizing written texts by author gender. Literary Linguist. Comput. 17(4), 401–412 (2002)Koppel, M., Schler, J., Bonchek-Dokow, E.: Measuring differentiability: unmasking pseudonymous authors. J. Mach. Learn. Res. 8, 1261–1276 (2007)Koppel, M., Winter, Y.: Determining if two documents are written by the same author. J. Am. Soc. Inf. Sci. Technol. 65(1), 178–187 (2014)Layton, R., Watters, P., Dazeley, R.: Automated unsupervised authorship analysis using evidence accumulation clustering. Nat. Lang. Eng. 19(1), 95–120 (2013)López-Monroy, A.P., Montes-y Gómez, M., Jair-Escalante, H., Villasenor-Pineda, L.V.: Using intra-profile information for author profiling-notebook for PAN at CLEF 2014. In: Working Notes Papers of the CLEF 2014 Evaluation Labs. CEUR-WS.org, vol. 1180 (2014)López-Monroy, A.P., Montes-y Gómez, M., Jair-Escalante, H., Villasenor-Pineda, L., Villatoro-Tello, E.: INAOE’s participation at PAN’13: author profiling task-notebook for PAN at CLEF 2013. In: Working Notes Papers of the CLEF 2013 Evaluation Labs. CEUR-WS.org, vol. 1179 (2013)Luyckx, K., Daelemans, W.: Authorship attribution and verification with many authors and limited data. In: Proceedings of COLING (2008)Maharjan, S., Shrestha, P., Solorio, T., Hasan, R.: A straightforward author profiling approach in MapReduce. In: Bazzan, A.L.C., Pichara, K. (eds.) IBERAMIA 2014. LNCS, vol. 8864, pp. 95–107. Springer, Heidelberg (2014)Mansoorizadeh, M.: Submission to the author obfuscation task at PAN 2016. In: Conference and Labs of the Evaluation Forum, CLEF (2016)Eissen, S.M., Stein, B.: Intrinsic plagiarism detection. In: Lalmas, M., MacFarlane, A., Rüger, S.M., Tombros, A., Tsikrika, T., Yavlinsky, A. (eds.) ECIR 2006. LNCS, vol. 3936, pp. 565–569. Springer, Heidelberg (2006)Mihaylova, T., Karadjov, G., Nakov, P., Kiprov, Y., Georgiev, G., Koychev, I.: SU@PAN’2016: author obfuscation-notebook for PAN at CLEF 2016. In: Conference and Labs of the Evaluation Forum, CLEF (2016)Miro, X.A., Bozonnet, S., Evans, N., Fredouille, C., Friedland, G., Vinyals, O.: Speaker diarization: a review of recent research. Audio Speech Language Process. IEEE Trans. 20(2), 356–370 (2012)Moreau, E., Jayapal, A., Lynch, G., Vogel, C.: Author verification: basic stacked generalization applied to predictions from a set of heterogeneous learners. In: Working Notes Papers of the CLEF 2015 Evaluation Labs. CEUR-WS.org, vol. 1391 (2015)Nguyen, D., Gravel, R., Trieschnigg, D., Meder, T.: How old do you think I am? a study of language and age in twitter. In: Proceedings of ICWSM 13. AAAI (2013)Peñas, A., Rodrigo, A.: A Simple measure to assess non-response. In: Proceedings of HLT 2011 (2011)Pennebaker, J.W., Mehl, M.R., Niederhoffer, K.G.: Psychological aspects of natural language use: our words, our selves. Ann. Rev. Psychol. 54(1), 547–577 (2003)Potthast, M., Barrón-Cedeño, A., Eiselt, A., Stein, B., Rosso, P.: Overview of the 2nd international competition on plagiarism detection. In: Working Notes Papers of the CLEF 2010 Evaluation Labs (2010)Potthast, M., Barrón-Cedeño, A., Stein, B., Rosso, P.: Cross-language plagiarism detection. Lang. Resour. Eval. (LREC) 45, 45–62 (2011)Potthast, M., Eiselt, A., Barrón-Cedeño, A., Stein, B., Rosso, P.: Overview of the 3rd international competition on plagiarism detection. In: Working Notes Papers of the CLEF 2011 Evaluation Labs (2011)Potthast, M., Gollub, T., Hagen, M., Graßegger, J., Kiesel, J., Michel, M., Oberländer, A., Tippmann, M., Barrón-Cedeño, A., Gupta, P., Rosso, P., Stein, B.: Overview of the 4th international competition on plagiarism detection. In: Working Notes Papers of the CLEF 2012 Evaluation Labs (2012)Potthast, M., Gollub, T., Hagen, M., Tippmann, M., Kiesel, J., Rosso, P., Stamatatos, E., Stein, B.: Overview of the 5th international competition on plagiarism detection. In: Working Notes Papers of the CLEF 2013 Evaluation Labs. CEUR-WS.org, vol. 1179 (2013)Potthast, M., Gollub, T., Rangel, F., Rosso, P., Stamatatos, E., Stein, B.: Improving the reproducibility of PAN’s shared tasks: plagiarism detection, author identification, and author profiling. In: Kanoulas, E., Lupu, M., Clough, P., Sanderson, M., Hall, M., Hanbury, A., Toms, E. (eds.) CLEF 2014. LNCS, vol. 8685, pp. 268–299. Springer, Heidelberg (2014)Potthast, M., Hagen, M., Beyer, A., Busse, M., Tippmann, M., Rosso, P., Stein, B.: Overview of the 6th international competition on plagiarism detection. In: Working Notes Papers of the CLEF 2014 Evaluation Labs. CEUR-WS.org, vol. 1180 (2014)Potthast, M., Hagen, M., Stein, B.: Author obfuscation: attacking the state of the art in authorship verification. In: CLEF 2016 Working Notes. CEUR-WS.org (2016)Potthast, M., Göring, S., Rosso, P., Stein, B.: Towards data submissions for shared tasks: first experiences for the task of text alignment. In: Working Notes Papers of the CLEF 2015 Evaluation Labs. CEUR-WS.org, vol. 1391 (2015)Potthast, M., Hagen, M., Stein, B., Graßegger, J., Michel, M., Tippmann, M., Welsch, C.: ChatNoir: a search engine for the ClueWeb09 corpus. In: Proceedings of SIGIR 12. ACM (2012)Potthast, M., Hagen, M., Völske, M., Stein, B.: Crowdsourcing interaction logs to understand text reuse from the web. In: Proceedings of ACL 13. ACL (2013)Potthast, M., Stein, B., Barrón-Cedeño, A., Rosso, P.: An evaluation framework for plagiarism detection. In: Proceedings of COLING 10. ACL (2010)Potthast, M., Stein, B., Eiselt, A., Barrón-Cedeño, A., Rosso, P.: Overview of the 1st international competition on plagiarism detection. In: Proceedings of PAN at SEPLN 09. CEUR-WS.org 502 (2009)Rangel, F., Rosso, P.: On the impact of emotions on author profiling. Inf. Process. Manage. Spec. Issue Emot. Sentiment Soc. Expressive Media 52(1), 73–92 (2016)Rangel, F., Rosso, P.: On the multilingual and genre robustness of emographs for author profiling in social media. In: Mothe, J., et al. (eds.) CLEF 2015. LNCS, vol. 9283, pp. 274–280. Springer, Heidelberg (2015). doi: 10.1007/978-3-319-24027-5_28Rangel, F., Rosso, P., Celli, F., Potthast, M., Stein, B., Daelemans, W.: Overview of the 3rd author profiling task at PAN 2015. In: Working Notes Papers of the CLEF 2015 Evaluation Labs. CEUR-WS.org, vol. 1391 (2015)Rangel, F., Rosso, P., Chugur, I., Potthast, M., Trenkmann, M., Stein, B., Verhoeven, B., Daelemans, W.: Overview of the 2nd author profiling task at PAN 2014. In: Working Notes Papers of the CLEF 2014 Evaluation Labs. CEUR-WS.org, vol. 1180 (2014)Rangel, F., Rosso, P., Koppel, M., Stamatatos, E., Inches, G.: Overview of the author profiling task at PAN 2013–notebook for PAN at CLEF 2013. In: Working Notes Papers of the CLEF 2013 Evaluation Labs. CEUR-WS.org, vol. 1179 (2013)Rangel, F., Rosso, P., Verhoeven, B., Daelemans, W., Potthast, M., Stein, B.: Overview of the 4th author profiling task at PAN 2016: cross-genre evaluations. In: CLEF 2016 Working Notes. CEUR-WS.org (2016)Samdani, R., Chang, K., Roth, D.: A discriminative latent variable model for online clustering. 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Drawing Elena Ferrante's Profile. Workshop Proceedings, Padova, 7 September 2017

Elena Ferrante is an internationally acclaimed Italian novelist whose real identity has been kept secret by E/O publishing house for more than 25 years. Owing to her popularity, major Italian and foreign newspapers have long tried to discover her real identity. However, only a few attempts have been made to foster a scientific debate on her work. In 2016, Arjuna Tuzzi and Michele Cortelazzo led an Italian research team that conducted a preliminary study and collected a well-founded, large corpus of Italian novels comprising 150 works published in the last 30 years by 40 different authors. Moreover, they shared their data with a select group of international experts on authorship attribution, profiling, and analysis of textual data: Maciej Eder and Jan Rybicki (Poland), Patrick Juola (United States), Vittorio Loreto and his research team, Margherita Lalli and Francesca Tria (Italy), George Mikros (Greece), Pierre Ratinaud (France), and Jacques Savoy (Switzerland). The chapters of this volume report the results of this endeavour that were first presented during the international workshop Drawing Elena Ferrante's Profile in Padua on 7 September 2017 as part of the 3rd IQLA-GIAT Summer School in Quantitative Analysis of Textual Data. The fascinating research findings suggest that Elena Ferrante\u2019s work definitely deserves \u201cmany hands\u201d as well as an extensive effort to understand her distinct writing style and the reasons for her worldwide success

A multi-class approach for ranking graph nodes: models and experiments with incomplete data

After the phenomenal success of the PageRank algorithm, many researchers have extended the PageRank approach to ranking graphs with richer structures beside the simple linkage structure. In some scenarios we have to deal with multi-parameters data where each node has additional features and there are relationships between such features. This paper stems from the need of a systematic approach when dealing with multi-parameter data. We propose models and ranking algorithms which can be used with little adjustments for a large variety of networks (bibliographic data, patent data, twitter and social data, healthcare data). In this paper we focus on several aspects which have not been addressed in the literature: (1) we propose different models for ranking multi-parameters data and a class of numerical algorithms for efficiently computing the ranking score of such models, (2) by analyzing the stability and convergence properties of the numerical schemes we tune a fast and stable technique for the ranking problem, (3) we consider the issue of the robustness of our models when data are incomplete. The comparison of the rank on the incomplete data with the rank on the full structure shows that our models compute consistent rankings whose correlation is up to 60% when just 10% of the links of the attributes are maintained suggesting the suitability of our model also when the data are incomplete