Proceedings of the Second Workshop on Computational Modeling of People’s Opinions, Personality, and Emotions in Social Media

Abstract

The idea of organizing PEOPLES stemmed from two related observations, namely the availability of large amounts of spontaneous data covering a range of personal aspects and the fact that such aspects are usually studied in isolation. Social media users nowadays freely express what is on their mind at any moment in time, at any location, and about virtually anything. These large amounts of spontaneously produced texts open up a unique opportunity to learn more about such users, e.g., predicting demographic variables (age, gender), but also personality types, as well as emotions and opinion expressions. This observation is not new, of course, and this opportunity has largely been exploited in the recent years, with abundant works on sentiment analysis, emotion detection, and personality. However, such traits of human personality and behavior have indeed attracted a substantial amount of attention but have been mostly studied in isolation, often in different -but related -communities, such as NLP, CL, AI. Therefore, we thought that the time was ripe to bring these communities a step closer to study people's traits and expressions jointly and in their interplay on such large volumes of available data.The communities' response, with 25 received submissions coming from 11 different countries and going well beyond typical NLP topics, proves again this year that there is wide interest at this intersection, and we are happy to be able to provide a context for exchanging ideas.Following the reviewers's advice, 14 papers were selected for inclusion in the proceedings. They cover a wide range of topics related to the three main PEOPLES themes (personality, emotion and opinion), their interaction and the impact of their modeling on social aspects like well-being, political preferences, humor and language use.To further enrich this volume, we additionally invited our keynote speakers to submit position papers that accompany their talks, and are excited that both of our keynotes submitted excellent papers touching upon issues of making NLP models more demographically aware and how researchers from related fields such as demography can benefit from NLP techniques.We hope that this is just the second edition of what will become series of workshops bringing together researchers in Computational Linguistics, Natural Language Processing and Computational Social Science, who share an interest in personality, opinion and emotion detection, and especially in researching the intertwining of such traits and expressions.We would like to thank our program committee consisting of 33 researchers from a variety of backgrounds for their insightful and constructive reviews. Without their support, this workshop would not have been possible. In addition, we thank all authors for submitting papers and making PEOPLES a big success. Also thanks to our two invited speakers, Dirk Hovy and Letizia Mencarini (Bocconi University, Italy), for having accepted to come to the workshop and share their expertise and ideas on PEOPLES' topics. We thank NAACL for...

Automatic Categorization of LGBT User Profiles on Twitter with Machine Learning

“…First, while other research developed binary classifiers, this paper offers a multi-label classifier to categorize users. For example, one study identifies individual and organization users [81]. Second, this study illustrates that the used traditional machine learning methods in this research offer better performance than deep learning using CNN for categorizing LGBT users using bio and profile features.…”