Overview of the Author Profiling Task at PAN 2013

[EN] This overview presents the framework and results for the Author Profiling task at PAN 2013. We describe in detail the corpus and its characteristics, and the evaluation framework we used to measure the participants performance to solve the problem of identifying age and gender from anonymous texts. Finally, the approaches of the 21 participants and their results are described.The author profiling task @PAN-2013 was an activity of the WIQ-EI IRSES project (Grant No. 269180) within the FP 7 Marie Curie People Framework of the European Commission. We want to thank the Forensic Lab of the Universitat Pompeu Fabra Barcelona for sponsoring the award for the winner team. The work of the first author was partially funded by Autoritas Consulting SA and by Ministerio de Economía y Competitividad de España under grant ECOPORTUNITY IPT-2012-1220-430000. The work of the second author was in the framework the DIANA-APPLICATIONS-Finding Hidden Knowledge in Texts: Applications (TIN2012-38603-C02-01) project, and the VLC/CAMPUS Microcluster on Multimodal Interaction in Intelligent Systems. The work of fifth author was funded in part by the Swiss National Science Foundation (SNF) project "Mining Conversational Content for Topic Modelling and Author Identification (ChatMiner)" under grant number 200021_130208.Rangel, F.; Rosso, P.; Koppel, M.; Stamatatos, E.; Inches, G. (2013). Overview of the Author Profiling Task at PAN 2013. CLEF Conference on Multilingual and Multimodal Information Access Evaluation. 352-365. http://hdl.handle.net/10251/46636S35236

DAEDALUS at PAN 2014: Guessing tweet author's gender and age

This paper describes our participation at PAN 2014 author profiling task. Our idea was to define, develop and evaluate a simple machine learning classifier able to guess the gender and the age of a given user based on his/her texts, which could become part of the solution portfolio of the company. We were interested in finding not the best possible classifier that achieves the highest accuracy, but to find the optimum balance between performance and throughput using the most simple strategy and less dependent of external systems. Results show that our software using Naive Bayes Multinomial with a term vector model representation of the text is ranked quite well among the rest of participants in terms of accuracy

On the multilingual and genre robustness of EmoGraphs for author profiling in social media

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-24027-5_28Author profiling aims at identifying different traits such as age and gender of an author on the basis of her writings. We propose the novel EmoGraph graph-based approach where morphosyntactic categories are enriched with semantic and affective information. In this work we focus on testing the robustness of EmoGraphs when applied to age and gender identification. Results with PAN-AP-14 corpus show the competitiveness of the representation over genres and languages. Finally, some interesting insights are shown, for example with topic and emotion bounded genres such as hotel reviews.The research has been carried out in the framework of the European Commission WIQ-EI IRSES (no. 269180) and DIANA - Finding Hidden Knowledge in Texts (TIN2012-38603-C02) projects. The work of the first author was partially funded by Autoritas Consulting SA and by Spanish Ministry of Economics under grant ECOPORTUNITY IPT-2012-1220-430000.Rangel, F.; Rosso, P. (2015). On the multilingual and genre robustness of EmoGraphs for author profiling in social media. En Experimental IR Meets Multilinguality, Multimodality, and Interaction: 6th International Conference of the CLEF Association, CLEF'15, Toulouse, France, September 8-11, 2015, Proceedings. Springer International Publishing. 274-280. https://doi.org/10.1007/978-3-319-24027-5_28S274280Argamon, S., Koppel, M., Fine, J., Shimoni, A.: Gender, genre, and writing style informal written texts. TEXT 23, 321–346 (2003)Levin, B.: English Verb Classes and Alternations. University of Chicago Press, Chicago (1993)Mohammad, S.M., Yang, T.: Tracking sentiment in mail: how gender differ on emotional axes. In: Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis (2011)Pennebaker, J.W.: The Secret Life of Pronouns: What Our Words Say About Us. Bloomsbury Press (2011)Rangel, F., Rosso, P.: On the impact of emotions on author profiling. Information Processing & Management, Special Issue on Emotion and Sentiment in Social and Expressive Media (in press, 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: Cappellato L., Ferro N., Halvey M., Kraaij, W. (eds.) CLEF 2014 Labs and Workshops, Notebook Papers. 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. In: Forner, P., Navigli, R., Tufis, D. (eds.) Notebook Papers of CLEF 2013 LABs and Workshops. CEUR-WS.org, vol. 1179 (2013)Sidorov, G., Miranda-Jimnez, S., Viveros-Jimnez, F., Gelbukh, F., Castro-Snchez, N., Velsquez, F., Daz-Rangel, I., Surez-Guerra, S., Trevio, A., Gordon-Miranda, J.: Empirical study of opinion mining in spanish tweets. In: 11th Mexican International Conference on Artificial Intelligence, MICAI, pp. 1–4 (2012)Strapparava, C., Valitutti, A.: Wordnet-affect: an affective extension of wordnet. In: Proceedings of the 4th International Conference on Language Resources and Evaluation, Lisbon (2004

Vector-based word representations for sentiment analysis: a comparative study

New applications of text categorization methods like opinion mining and sentiment analysis, author profiling and plagiarism detection requires more elaborated and effective document representation models than classical Information Retrieval approaches like the Bag of Words representation. In this context, word representation models in general and vector-based word representations in particular have gained increasing interest to overcome or alleviate some of the limitations that Bag of Words-based representations exhibit. In this article, we analyze the use of several vector-based word representations in a sentiment analysis task with movie reviews. Experimental results show the effectiveness of some vector-based word representations in comparison to standard Bag of Words representations. In particular, the Second Order Attributes representation seems to be very robust and effective because independently the classifier used with, the results are good.XIII Workshop Bases de datos y Minería de Datos (WBDMD).Red de Universidades con Carreras en Informática (RedUNCI

Vector-based word representations for sentiment analysis: a comparative study

New applications of text categorization methods like opinion mining and sentiment analysis, author profiling and plagiarism detection requires more elaborated and effective document representation models than classical Information Retrieval approaches like the Bag of Words representation. In this context, word representation models in general and vector-based word representations in particular have gained increasing interest to overcome or alleviate some of the limitations that Bag of Words-based representations exhibit. In this article, we analyze the use of several vector-based word representations in a sentiment analysis task with movie reviews. Experimental results show the effectiveness of some vector-based word representations in comparison to standard Bag of Words representations. In particular, the Second Order Attributes representation seems to be very robust and effective because independently the classifier used with, the results are good.XIII Workshop Bases de datos y Minería de Datos (WBDMD).Red de Universidades con Carreras en Informática (RedUNCI

A Spanish text corpus for the author profiling task

Author Profiling is the task of predicting characteristics of the author of a text, such as age, gender, personality, native language, etc. This is a task of growing importance due to its potential applications in security, crime and marketing, among others. One of the main difficulties in this field is the lack of reliable text collections (corpora) to train and test automatically derived classifiers, in particular in specific languages such as Spanish. Although some recent data sets were generated for the PAN competitions, these documents have a lot of “noise” that prevent researchers from obtaining more general conclusions about this task when more formal documents are used. In this context, this work proposes and describes SpanText, a data collection of formal texts in Spanish language which is, as far as we know, the first collection with these characteristics for the author profiling task. Besides, an experimental study is carried out where the difference in performance obtained with formal and informal texts is clearly established and opens interesting research lines to get a deeper understanding of the particularities that each type of documents poses to the author profiling task.XI Workshop Bases de Datos y Minería de DatosRed de Universidades con Carreras de Informática (RedUNCI