Titlebook: Natural Language Processing and Information Systems; 23rd International C Max Silberztein,Faten Atigui,Farid Meziane Conference proceedings

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Type-1-Diabetes

Stance Evolution and Twitter Interactions in an Italian Political Debatessue of developing automated systems for a deep analysis of users’ generated contents and interactions is becoming increasingly relevant. In particular, when we focus on the domain of online political debates, interest for the automatic classification of users’ stance towards a given entity, like a

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Identifying and Classifying Influencers in Twitter only with Textual Information rely on metrics provided by Twitter such as followers, retweets, etc. In this work we follow the research initiated at RepLab 2014, but relying only on the textual content of tweets. Moreover, we have proposed a workflow to identify influencers and classify them into an interest group from a reputa

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CYN

PTCA635

Automatic Identification and Classification of Misogynistic Language on Twitter discussions about ethnicity, religion, gender identity and sexual orientation. In this paper, we address the problem of automatic detection and categorization of misogynous language in online social media. The main contribution of this paper is two-fold: (1) a corpus of misogynous tweets, labelled