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COMPUTATIONAL MODELING OF PEOPLE’S OPINIONS, PERSONALITY, AND EMOTIONS IN SOCIAL MEDIA

@ COLING 2020, Barcelona
with the support of

CELI             RUG

Important Dates

Submission deadline September 14, 2020
September 21, 2020 (AoE)
Notification June 24, 2020
October 16, 2020
Camera ready July 11, 2020
November 1, 2020
Workshop September 14, 2020
December 13, 2020


Earlier editions

2018 @NAACL, New Orleans, US
2016 @COLING, Osaka, Japan


THIRD WORKSHOP ON COMPUTATIONAL MODELING OF PEOPLE’S OPINIONS, PERSONALITY, AND EMOTIONS IN SOCIAL MEDIA

Workshop co-located with COLING - Barcelona

December 13, 2020

NEWS

On 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 social media users, e.g., predicting socio-demographic variables (age, gender, profession, education), personality types, as well as emotions and opinion expressions. Indeed, this excellent opportunity has materialized in a large and growing number of recent workshops held at different Natural Language Processing, Artificial Intelligence, Semantic Web, and Information Retrieval venues, for example WASSA (focusing on sentiment and social media), PAN (focusing on author profiling like personality) and ESSEM (focusing on emotions in AI), including the organization of shared tasks such asat SemEval with a special sentiment track. However, such aspects of human personality and behavior have been mostly studied in isolation, often in different—but related—communities. PEOPLES aims at bringing these diverse communities a step closer to each other, to study people's traits and expressions jointly and in their interplay.

Indeed, the traits in the focus of PEOPLES can be seen as characterizing the whole person and should be studied together. Contextually, one should study how their interaction, and their computational modelling impact both natural language processing and society. This also in view of recent active discussions regarding ethical and bias-related aspects in NLP, which strongly relate to the traits that the PEOPLES workshop focuses on.

PEOPLES 2020 would be the continuation of successful editions that were held at COLING 2016 and NAACL 2018, by continuing to provide a forum for researchers who share an interest in personality, opinion and emotion detection, as well as the impact of this work on society.

We will encourage the submission of long (9 pages) and short (4 pages) research papers, including opinion statements. We will especially welcome views from different fields, and will welcome submissions related but not limited to the following topics:

UPDATE: We also very much welcome research that focuses on how the usual PEOPLES dimensions might have changed or might be changing due to the special COVID-related circumstances. For example, how relevant traits might be represented differently now with respect to 'normal' times.

Keynote speakers

Accepted Papers

Paper Submission

We invite submissions of up to nine (9) pages maximum, plus bibliography for long papers and four (4) pages, plus bibliography, for short papers. Position papers can be both long and short. For all paper types, unlimited pages for references are allowed. All papers should be electronically submitted in PDF format via the START system, available at:

https://www.softconf.com/coling2020/PEOPLES/

Submissions must be anonymous and follow the COLING 2020 style templates. The review process will be double-blind.

Programme Committee

General Chairs and Organisers

Publicity and Publication Chair

If have any enquiries/comments about the workshop or the submission procedure, please just contact us via email:
peoples.wksh at gmail dot com


You can also follow us on Facebook!

This workshop is organised with the support of CELI Language Technology and the Computational Linguistics group of CLCG, University of Groningen. Would you be interesting in becoming sponsor? Please reach out!


CELI             RUG