| { | |
| "paper_id": "2020", | |
| "header": { | |
| "generated_with": "S2ORC 1.0.0", | |
| "date_generated": "2023-01-19T08:45:07.868411Z" | |
| }, | |
| "title": "Social Interpretations of Interpersonal Communication", | |
| "authors": [ | |
| { | |
| "first": "Viviana", | |
| "middle": [], | |
| "last": "Patti", | |
| "suffix": "", | |
| "affiliation": {}, | |
| "email": "" | |
| }, | |
| { | |
| "first": "Jeremy", | |
| "middle": [], | |
| "last": "Barnes", | |
| "suffix": "", | |
| "affiliation": {}, | |
| "email": "" | |
| }, | |
| { | |
| "first": "Maria", | |
| "middle": [], | |
| "last": "Barrett", | |
| "suffix": "", | |
| "affiliation": {}, | |
| "email": "" | |
| }, | |
| { | |
| "first": "Roman", | |
| "middle": [], | |
| "last": "Klinger", | |
| "suffix": "", | |
| "affiliation": {}, | |
| "email": "" | |
| }, | |
| { | |
| "first": "Florian", | |
| "middle": [], | |
| "last": "Kunneman", | |
| "suffix": "", | |
| "affiliation": {}, | |
| "email": "" | |
| }, | |
| { | |
| "first": "Dong", | |
| "middle": [], | |
| "last": "Nguyen", | |
| "suffix": "", | |
| "affiliation": {}, | |
| "email": "" | |
| }, | |
| { | |
| "first": "Paolo", | |
| "middle": [], | |
| "last": "Rosso", | |
| "suffix": "", | |
| "affiliation": {}, | |
| "email": "" | |
| }, | |
| { | |
| "first": "Ingmar", | |
| "middle": [], | |
| "last": "Weber", | |
| "suffix": "", | |
| "affiliation": {}, | |
| "email": "" | |
| }, | |
| { | |
| "first": "David", | |
| "middle": [], | |
| "last": "Jurgens", | |
| "suffix": "", | |
| "affiliation": {}, | |
| "email": "" | |
| } | |
| ], | |
| "year": "", | |
| "venue": null, | |
| "identifiers": {}, | |
| "abstract": "", | |
| "pdf_parse": { | |
| "paper_id": "2020", | |
| "_pdf_hash": "", | |
| "abstract": [], | |
| "body_text": [ | |
| { | |
| "text": "Welcome to the third edition of PEOPLES, the Workshop on Computational Modeling of People's Opinions, Personality and Emotions in Social Media, co-located with the 28th International Conference on Computational Linguistics (COLING 2020) . PEOPLES 2020 is the continuation of a successful series of workshops that were held at the 26th International Conference on Computational Linguistics (COLING 2016) in Osaka, Japan, and at the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2018), New Orleans, USA, aimed at providing a forum for researchers who share an interest in personality, opinion and emotion detection, as well as the impact of work in this research field on society.", | |
| "cite_spans": [ | |
| { | |
| "start": 223, | |
| "end": 236, | |
| "text": "(COLING 2020)", | |
| "ref_id": null | |
| } | |
| ], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Preface", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "The communities' response, with 32 received submissions coming from 15 different countries from Asia-Pacific, Europe and the USA, and going well beyond typical Natural Language Processing topics, proves again this year that there is wide interest at the intersection of fields studying sentiment analysis, emotion detection, and personality in disciplines such Computational Linguistics, Natural Language Processing, and Computational Social Science, and we are happy to be able to provide a context for exchanging ideas. Also, we deem it important to provide a forum where crucial discussion about ethical aspects related to the research involving the PEOPLES traits can find a place to be, and to grow.", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Preface", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "Following the reviewers's advice, 15 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 modelling on social aspects like well-being, inclusion, political preferences and language use. This year, we also noticed that multilinguality is definitely a key issue, with a large variety of languages represented in the research described. Additionally, we had specifically mentioned in the call that we would very much welcome research focusing on how the usual PEOPLES dimensions might have changed or might be changing due to the special COVID-related circumstances. Clearly this is a dominant topic in the community from several viewpoints, with at least four papers specifically discussing pandemic-related research. We are extremely grateful to David Jurgens from the University of Michigan for giving a keynote talk. His work at the interesection of NLP and Computational Social Science enriches the workshop program.", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Preface", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "We would like to thank our program committee consisting of 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. A big thanks to our publicity and publication chair Esin Durmus, Cornell University, for her endless support and for compiling these proceedings, particularly in these difficult pandemic times.", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Preface", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "We thank COLING for hosting us again, this time virtually, and in particular the local organizers for their support. Thanks for all the extra efforts of moving the conference and all workshops online, unlike the original plans. We hope you and your family are all safe. Lastly, we are extremely grateful to our sponsors, CELI Language Technologies, and the Computational Linguistics group of the University of Groningen for their financial support.", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Preface", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "We look forward to welcoming you all at this fully virtual edition of PEOPLES 2020! Malvina, Viviana, Barbara, and Esin PEOPLES: https://peopleswksh.github.io/", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Preface", | |
| "sec_num": null | |
| } | |
| ], | |
| "back_matter": [], | |
| "bib_entries": { | |
| "BIBREF0": { | |
| "ref_id": "b0", | |
| "title": "Inferring Neuroticism of Twitter Users by Utilizing their Following Interests Joran Cornelisse", | |
| "authors": [], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Inferring Neuroticism of Twitter Users by Utilizing their Following Interests Joran Cornelisse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1", | |
| "links": null | |
| }, | |
| "BIBREF1": { | |
| "ref_id": "b1", | |
| "title": "Matching Theory and Data with Personal-ITY: What a Corpus of Italian YouTube Comments Reveals About Personality Elisa Bassignana, Malvina Nissim and Viviana Patti", | |
| "authors": [], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Matching Theory and Data with Personal-ITY: What a Corpus of Italian YouTube Comments Reveals About Personality Elisa Bassignana, Malvina Nissim and Viviana Patti . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11", | |
| "links": null | |
| }, | |
| "BIBREF2": { | |
| "ref_id": "b2", | |
| "title": "Blue Is Conscientious: Predicting User Traits From Instagram Image Data Lisa Branz, Patricia Brockmann and Annika Hinze", | |
| "authors": [], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Red Is Open-Minded, Blue Is Conscientious: Predicting User Traits From Instagram Image Data Lisa Branz, Patricia Brockmann and Annika Hinze . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23", | |
| "links": null | |
| }, | |
| "BIBREF3": { | |
| "ref_id": "b3", | |
| "title": "Persuasiveness of News Editorials depending on Ideology and Personality Roxanne El Baff", | |
| "authors": [ | |
| { | |
| "first": "Al", | |
| "middle": [], | |
| "last": "Khalid", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Benno", | |
| "middle": [], | |
| "last": "Khatib", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "", | |
| "middle": [], | |
| "last": "Stein", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "", | |
| "middle": [ | |
| ". . . . . . . . . . . . . . ." | |
| ], | |
| "last": "Henning Wachsmuth", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Persuasiveness of News Editorials depending on Ideology and Personality Roxanne El Baff, Khalid Al Khatib, Benno Stein and Henning Wachsmuth . . . . . . . . . . . . . . . . . . . 29", | |
| "links": null | |
| }, | |
| "BIBREF4": { | |
| "ref_id": "b4", | |
| "title": "Multilingual Hope Speech Detection Dataset for Equality", | |
| "authors": [ | |
| { | |
| "first": "", | |
| "middle": [], | |
| "last": "Hopeedi", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "HopeEDI: A Multilingual Hope Speech Detection Dataset for Equality, Diversity, and Inclusion Bharathi Raja Chakravarthi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41", | |
| "links": null | |
| }, | |
| "BIBREF5": { | |
| "ref_id": "b5", | |
| "title": "KanCMD: Kannada CodeMixed Dataset for Sentiment Analysis and Offensive Language Detection Adeep Hande, Ruba Priyadharshini and Bharathi Raja Chakravarthi", | |
| "authors": [], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "KanCMD: Kannada CodeMixed Dataset for Sentiment Analysis and Offensive Language Detection Adeep Hande, Ruba Priyadharshini and Bharathi Raja Chakravarthi. . . . . . . . . . . . . . . . . . . . . . . . . .54", | |
| "links": null | |
| }, | |
| "BIBREF6": { | |
| "ref_id": "b6", | |
| "title": "Contextual Augmentation of Pretrained Language Models for Emotion Recognition in Conversations Jonggu Kim", | |
| "authors": [ | |
| { | |
| "first": "Hyeonmok", | |
| "middle": [], | |
| "last": "Ko", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Saebom", | |
| "middle": [], | |
| "last": "Song", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Jiyeon", | |
| "middle": [], | |
| "last": "Jang", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": ".", | |
| "middle": [ | |
| "." | |
| ], | |
| "last": "Hong", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Contextual Augmentation of Pretrained Language Models for Emotion Recognition in Conversations Jonggu Kim, Hyeonmok Ko, seoha song, Saebom Jang and Jiyeon Hong . . . . . . . . . . . . . . . . . . . . . 64", | |
| "links": null | |
| }, | |
| "BIBREF7": { | |
| "ref_id": "b7", | |
| "title": "Social Media Unrest Prediction during the COVID-19 Pandemic: Neural Implicit Motive Pattern Recognition as Psychometric Signs of Severe Crises Dirk Johann\u00dfen and", | |
| "authors": [], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Social Media Unrest Prediction during the COVID-19 Pandemic: Neural Implicit Motive Pattern Recog- nition as Psychometric Signs of Severe Crises Dirk Johann\u00dfen and Chris Biemann . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74", | |
| "links": null | |
| }, | |
| "BIBREF8": { | |
| "ref_id": "b8", | |
| "title": "Topic and Emotion Development among Dutch COVID-19 Twitter Communities in the early Pandemic Boris Marinov", | |
| "authors": [ | |
| { | |
| "first": "Jennifer", | |
| "middle": [], | |
| "last": "Spenader", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": ".", | |
| "middle": [ | |
| "." | |
| ], | |
| "last": "Tommaso Caselli", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": null, | |
| "venue": "", | |
| "volume": "87", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Topic and Emotion Development among Dutch COVID-19 Twitter Communities in the early Pandemic Boris Marinov, Jennifer Spenader and Tommaso Caselli . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87", | |
| "links": null | |
| }, | |
| "BIBREF9": { | |
| "ref_id": "b9", | |
| "title": "Sentiments in Russian Medical Professional Discourse during the Covid-19 Pandemic Irina Ovchinnikova, Liana Ermakova and", | |
| "authors": [], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Sentiments in Russian Medical Professional Discourse during the Covid-19 Pandemic Irina Ovchinnikova, Liana Ermakova and Diana Nurbakova . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99", | |
| "links": null | |
| }, | |
| "BIBREF10": { | |
| "ref_id": "b10", | |
| "title": "Multilingual Emoticon Prediction of Tweets about COVID-19", | |
| "authors": [], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Multilingual Emoticon Prediction of Tweets about COVID-19", | |
| "links": null | |
| }, | |
| "BIBREF12": { | |
| "ref_id": "b12", | |
| "title": "Which Semantic Roles Enable Machine Learning to Infer the Emotions? Laura Ana Maria Oberl\u00e4nder", | |
| "authors": [ | |
| { | |
| "first": "", | |
| "middle": [], | |
| "last": "Experiencers", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "", | |
| "middle": [], | |
| "last": "Stimuli", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Kevin", | |
| "middle": [], | |
| "last": "Targets", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Roman", | |
| "middle": [], | |
| "last": "Reich", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": ".", | |
| "middle": [ | |
| "." | |
| ], | |
| "last": "Klinger", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Experiencers, Stimuli, or Targets: Which Semantic Roles Enable Machine Learning to Infer the Emo- tions? Laura Ana Maria Oberl\u00e4nder, Kevin Reich and Roman Klinger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119", | |
| "links": null | |
| }, | |
| "BIBREF13": { | |
| "ref_id": "b13", | |
| "title": "Robustness of Deep Learning under Strong Data Limitations Sven Buechel", | |
| "authors": [], | |
| "year": null, | |
| "venue": "", | |
| "volume": "100", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Learning Emotion from 100 Observations: Unexpected Robustness of Deep Learning under Strong Data Limitations Sven Buechel, Jo\u00e3o Sedoc, H. Andrew Schwartz and Lyle Ungar . . . . . . . . . . . . . . . . . . . . . . . . . . . 129", | |
| "links": null | |
| }, | |
| "BIBREF14": { | |
| "ref_id": "b14", | |
| "title": "Cross-lingual Emotion Intensity Prediction Irean Navas Alejo", | |
| "authors": [ | |
| { | |
| "first": "Toni", | |
| "middle": [], | |
| "last": "Badia", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Jeremy", | |
| "middle": [], | |
| "last": "Barnes", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": ".", | |
| "middle": [ | |
| "." | |
| ], | |
| "last": "", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Cross-lingual Emotion Intensity Prediction Irean Navas Alejo, Toni Badia and Jeremy Barnes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140", | |
| "links": null | |
| }, | |
| "BIBREF15": { | |
| "ref_id": "b15", | |
| "title": ":30 Topic and Emotion Development among Dutch COVID-19 Twitter Communities in the early Pandemic Boris Marinov", | |
| "authors": [ | |
| { | |
| "first": "Slovene", | |
| "middle": [], | |
| "last": "Dutch", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Ilia", | |
| "middle": [], | |
| "last": "Nikola Ljube\u0161i\u0107", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Darja", | |
| "middle": [], | |
| "last": "Markov", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Walter", | |
| "middle": [], | |
| "last": "Fi\u0161er", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "", | |
| "middle": [ | |
| ". . . . . . . . . . . . . . . . . . . . . . ." | |
| ], | |
| "last": "Daelemans", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": null, | |
| "venue": "Social Media Unrest Prediction during the COVID-19 Pandemic: Neural Implicit Motive Pattern Recognition as Psychometric Signs of Severe Crises Dirk Johann\u00dfen and Chris Biemann", | |
| "volume": "153", | |
| "issue": "", | |
| "pages": "50--68", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "The LiLaH Emotion Lexicon of Croatian, Dutch and Slovene Nikola Ljube\u0161i\u0107, Ilia Markov, Darja Fi\u0161er and Walter Daelemans . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 16:00-17:00 Session 3 16:00-16:45 Keynote: Social Interpretations of Interpersonal Communication David Jurgens (University of Michigan, US) 16:45-17:00 Break 17:00-18:00 Session 4 17:00-17:20 Social Media Unrest Prediction during the COVID-19 Pandemic: Neural Implicit Motive Pattern Recognition as Psychometric Signs of Severe Crises Dirk Johann\u00dfen and Chris Biemann 17:20-17:30 Topic and Emotion Development among Dutch COVID-19 Twitter Communities in the early Pandemic Boris Marinov, Jennifer Spenader and Tommaso Caselli 17:30-17:50 Sentiments in Russian Medical Professional Discourse during the Covid-19 Pan- demic Irina Ovchinnikova, Liana Ermakova and Diana Nurbakova 17:50-18:00 Multilingual Emoticon Prediction of Tweets about COVID-19", | |
| "links": null | |
| }, | |
| "BIBREF16": { | |
| "ref_id": "b16", | |
| "title": "Stimuli, or Targets: Which Semantic Roles Enable Machine Learning to Infer the Emotions? Laura Ana Maria Oberl\u00e4nder", | |
| "authors": [ | |
| { | |
| "first": "Stefanos", | |
| "middle": [], | |
| "last": "Stoikos", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Mike", | |
| "middle": [], | |
| "last": "Izbicki", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": null, | |
| "venue": "50 Cross-lingual Emotion Intensity Prediction Irean Navas Alejo, Toni Badia and Jeremy", | |
| "volume": "18", | |
| "issue": "", | |
| "pages": "50--69", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Stefanos Stoikos and Mike Izbicki 18:00-19:00 Session 5 18:00-18:20 Experiencers, Stimuli, or Targets: Which Semantic Roles Enable Machine Learning to Infer the Emotions? Laura Ana Maria Oberl\u00e4nder, Kevin Reich and Roman Klinger 18:20-18:30 Learning Emotion from 100 Observations: Unexpected Robustness of Deep Learn- ing under Strong Data Limitations Sven Buechel, Jo\u00e3o Sedoc, H. Andrew Schwartz and Lyle Ungar 18:30-18:50 Cross-lingual Emotion Intensity Prediction Irean Navas Alejo, Toni Badia and Jeremy Barnes 18:50-19:00 The LiLaH Emotion Lexicon of Croatian, Dutch and Slovene Nikola Ljube\u0161i\u0107, Ilia Markov, Darja Fi\u0161er and Walter Daelemans", | |
| "links": null | |
| } | |
| }, | |
| "ref_entries": {} | |
| } | |
| } |