Schedule

All times are local Toronto (UTC/GMT -4 hour)

Time Programmed Session
09:00 - 09:10 Opening Remarks
09:10 - 10:30 Oral presentation session 1
10:30 - 11:00 Coffee Break
11:00 - 12:30 Hybrid Poster Session
12:30 - 13:30 Invited Talk: David Jurgens - The Social Dimensions of Communication: How Context Shapes Language Use and Interpretation
13:30 - 14:30 Lunch Break
14:30 - 15:30 Shared Task Session
15:30 - 16:00 Coffee break
16:00 - 17:00 Invited Talk: Emily Öhman - Affective Datafication of Narratives: measuring affect, emotion, and mood in literary texts
17:00 - 18:00 Oral presentation session 2
18:00 - 18:15 Closing remarks and best paper award

Oral presentation session 1

  • 9:10 - 9:25 - A Fine Line Between Irony and Sincerity: Identifying Bias in Transformer Models for Irony Detection. Aaron Maladry, Els Lefever, Cynthia Van Hee and Veronique Hoste In-person
  • 9:25 - 9:40 - Towards Detecting Harmful Agendas in News Articles. Melanie Subbiah, Amrita Bhattacharjee, Yilun Hua, Tharindu Sandaruwan Kumarage, Huan Liu and Kathleen McKeown. In-person
  • 9:40 - 9:55 - Unsupervised Domain Adaptation using Lexical Transformations and Label Injection for Twitter Data. Akshat Gupta, Xiaomo Liu and Sameena Shah.Virtual
  • 9:55 - 10:10 - Context-Dependent Embedding Utterance Representations for Emotion Recognition in Conversations. Patrícia Pereira, Helena Silva Moniz, Isabel Dias and Joao Paulo Carvalho. In-person
  • 10:10 - 10:25 - Multilingual Language Models are not Multicultural: A Case Study in Emotion. Shreya Havaldar, Bhumika Singhal, Sunny Rai, Langchen Liu, Sharath Chandra Guntuku and Lyle Ungar. In-person

Hybrid poster session (11:00 - 12:30:)

All posters - in-person and virtual - (including the shared task posters not shown below) will be presented at the same time slot.

  • PESTO: A Post-User Fusion Network for Rumour Detection on Social Media. Erxue Min and Sophia Ananiadou.
  • Sentimental Matters - Predicting Literary Quality by Sentiment Analysis and Stylometric Features. Yuri Bizzoni, Pascale Feldkamp Moreira, Mads Rosendahl Thomsen and Kristoffer Nielbo.
  • You Are What You Read: Inferring Personality From Consumed Textual Content. Adam Sutton, Almog Simchon, Matthew Edwards and Stephan Lewandowsky.
  • UNIDECOR: A Unified Deception Corpus for Cross-Corpus Deception Detection. Aswathy Velutharambath and Roman Klinger.
  • Discourse Mode Categorization of Bengali Social Media Health Text. Salim Sazzed.
  • Emotion and Sentiment Guided Paraphrasing. Justin J Xie and Ameeta Agrawal.
  • Emotions in Spoken Language - Do we need acoustics? Nadine Probol and Margot Mieskes.
  • Understanding Emotion Valence is a Joint Deep Learning Task. Gabriel Roccabruna, Seyed Mahed Mousavi and Giuseppe Riccardi.
  • Czech-ing the News: Article Trustworthiness Dataset for Czech. Matyas Bohacek, Michal Bravansky, Filip Trhlík and Vaclav Moravec.
  • GSAC: A Gujarati Sentiment Analysis Corpus from Twitter. Monil Gokani and Radhika Mamidi.
  • An XAI Dataset for Mining the Sentimental Mood of the German Automotive Industry. Andrea Zielinski, Calvin Spolwind, Henning Kroll and Anna Grimm.
  • Examining Bias in Opinion Summarisation through the Perspective of Opinion Diversity. Nannan Huang, Lin Tian, Haytham M. Fayek and Xiuzhen Zhang.
  • Fluency Matters! Controllable Style Transfer with Syntax Guidance. Ji-Eun Han and Kyung-Ah Sohn.
  • ChatGPT for Suicide Risk Assessment on Social Media: Quantitative Evaluation of Model Performance, Potentials and Limitations. Hamideh Ghanadian, Isar Nejadgholi and Hussein Al Osman.
  • Transformer-based cynical expression detection in a corpus of Spanish YouTube reviews. Samuel Gonzalez-Lopez and Steven Bethard.
  • Combining Active Learning and Task Adaptation with BERT for Cost-Effective Annotation of Social Media Datasets. Jens Lemmens and Walter Daelemans.
  • Improving Dutch Vaccine Hesitancy Monitoring via Multi-Label Data Augmentation with GPT-3.5. Jens Van Nooten and Walter Daelemans.
  • Emotion Analysis of Tweets Banning Education in Afghanistan. Mohammad Ali Hussiny and Lilja Øvrelid.
  • Sentiment and Emotion Classification in Low-resource Settings. Jeremy Barnes.
  • Analyzing Subjectivity Using a Transformer-Based Regressor Trained on Naïve Speakers’ Judgements. Elena Savinova and Fermin Moscoso Del Prado.
  • ChatGPT is fun, but it is not funny! Humor is still challenging Large Language Models. Sophie Jentzsch and Kristian Kersting.
  • How to Control Sentiment in Text Generation: A Survey of the State-of-the-Art in Sentiment-Control Techniques. Michela Lorandi and Anya Belz.
  • Transformer-based Prediction of Emotional Reactions to Online Social Network Posts. Irene Benedetto, Moreno La Quatra, Luca Cagliero, Luca Vassio and Martino Trevisan.
  • Transfer Learning for Code-Mixed Data: Do Pretraining Languages Matter? Kushal Tatariya, Heather Lent and Miryam De Lhoneux.
  • Can ChatGPT Understand Causal Language in Science Claims? Yuheun Kim, Lu Guo, Bei Yu and Yingya Li.
  • Systematic Evaluation of GPT-3 for Zero-Shot Personality Estimation. Adithya V Ganesan, Yash Kumar Lal, August Håkan Nilsson and H. Schwartz.
  • Utterance Emotion Dynamics in Children’s Poems: Emotional Changes across Age. Daniela Teodorescu, Alona Fyshe and Saif M. Mohammad.
  • Annotating and Training for Population Subjective Views. Maria Alexeeva, Caroline Hyland, Keith Alcock, Allegra A. Beal Cohen, Hubert Kanyamahanga, Isaac Kobby Anni and Mihai Surdeanu.
  • Exploration of Contrastive Learning Strategies toward more Robust Stance Detection. Udhaya Kumar Rajendran and Amine Trabelsi.
  • Adapting Emotion Detection to Analyze Influence Campaigns on Social Media. Ankita Bhaumik, Andy Bernhardt, Gregorios A Katsios, Ning Sa and Tomek Strzalkowski.
  • Not Just Iconic: Emoji Interpretation is Shaped by Use. Brianna O’Boyle and Gabriel Doyle.
  • The Paradox of Multilingual Emotion Detection. Luna De Bruyne.
  • Sadness and Anxiety Language in Reddit Messages Before and After Quitting a Job. Molly E. Ireland, Micah Iserman and Kiki Rose Adams.
  • Communicating Climate Change: A Comparison Between Tweets and Speeches by German Members of Parliament. Robin Schaefer, Christoph Maximilian Abels, Stephan Lewandowsky and Manfred Stede

Shared Task

  • Findings of WASSA 2023 Shared Task on Empathy, Emotion and Personality Detection in Conversation and Reactions to News Articles. Valentin Barriere, João Sedoc, Shabnam Tafreshi and Salvatore Giorgi
  • HIT-SCIR at WASSA 2023: Empathy and Emotion Analysis at the Utterance-Level and the Essay-Level. FXin Lu, Zhuojun Li, Yanpeng Tong, Yanyan Zhao and Bing Qin.
  • Findings of WASSA 2023 Shared Task: Multi-Label and Multi-Class Emotion Classification on Code-Mixed Text Messages. Iqra Ameer, Necva Bölücü, Hua Xu and Ali Al Bataineh.
  • YNU-HPCC at WASSA 2023: Using Text-Mixed Data Augmentation for Emotion Classification on Code-Mixed Text Message. Xuqiao Ran, You Zhang, Jin Wang, Dan Xu and Xuejie Zhang.

Invited Talk: David Jurgens

The Social Dimensions of Communication: How Context Shapes Language Use and Interpretation

NLP studies of communication often focus on the individual: What we say, when we say it, and how we say it. Yet, the larger social context beyond the individual also plays an important role in our communication — just think of things you can say to your friends but not your parents. How does the social context influence our communication style and content? In this talk, I will describe recent work from my group studying the influence of this context by examining how we choose who to communicate with, how we interpret messages, and how we phrase messages. Across these studies, I will motivate a causal approach for NLP when studying communication behavior to move beyond descriptive analyses to more precise estimates of the effects of social context.

Bio

David Jurgens is an assistant professor at the University of Michigan School of Information where he leads the Blablablab. He holds a PhD in Computer Science from the University of California, Los Angeles. His research focuses on the intersection between NLP and computational social science venues and has won the Cozzarelli Prize, Cialdini Prize, best paper at ICWSM and W-NUT, and best paper nomination at ACL and Web Science.

Invited Talk: Emily Öhman

Affective Datafication of Narratives: measuring affect, emotion, and mood in literary texts

Our understanding of affect, emotion, and mood - despite the distinct nuances each term holds - often becomes blurred, leading to a usage that is almost interchangeable, particularly within sentiment analysis and NLP. In contrast, traditional fields such as literary studies hold on to more rigid definitions of these terms and how they are understood both in theory and practice. This can easily foster a disconnect between emerging fields such as computational literary studies and the more established qualitative counterparts. This disconnect unfortunately hinders the free exchange of innovative research ideas and methodologies. This talk aims to bridge this gap, highlighting the unique roles of affect, emotion, and mood in narratives and how we can attempt to robustly measure them. We will delve into the interplay of these terms, exploring how they shape and are shaped by authors, readers, and researchers focusing on the operationalization and translation involved in the analysis of emotion-laden phenomena. This exploration will underscore the need for a more comprehensive and nuanced understanding, encouraging synergy between tradition and innovation in emotion detection in general and literary research in particular.

Bio

Emily Öhman is currently a tenure-track Assistant professor of Digital Humanities at Waseda University. She received her PhD in Language Technology from the University of Helsinki, where her work centered on building multilingual emotion detection resources for downstream tasks.

Her research interests lie within digital humanities and NLP, more specifically sentiment analysis and emotion detection, often doing collaborations with various disciplines such as history, literature, and political science. Her recent projects have focused on negative emotions in literature using affect as a proxy for the literary concept of mood and most recently contrasting the semantic spaces of shame and guilt in Japanese and English social media posts.

Oral presentation session 2

  • 17:00 - 17:15 - Identifying Slurs and Lexical Hate Speech via Light-Weight Dimension Projection in Embedding Space. Sanne Hoeken, Sina Zarrieß and Ozge Alacam. In-person
  • 17:15 - 17:30 - Modelling Political Aggression on Social Media Platforms. Akash Rawat, Nazia Nafis, Dnyaneshwar Bhadane, Diptesh Kanojia and Rudra Murthy. Virtual
  • 17:30 - 17:45 - Instruction Tuning for Few-Shot Aspect-Based Sentiment Analysis. Siddharth Varia, Shuai Wang, Kishaloy Halder, Robert Vacareanu, Miguel Ballesteros, Yassine Benajiba, Neha Anna John, Rishita Anubhai, Smaranda Muresan and Dan Roth. Virtual
  • 17:45 - 18:00 - Painsight: An Extendable Opinion Mining Framework for Detecting Pain Points Based on Online Customer Reviews Yukyung Lee, Jaehee Kim, Doyoon Kim, Yookyung Kho, Younsun Kim and Pilsung Kang. Virtual