Archive
13th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis
News
July 14: The proceedings are temporarily available here until they are fully included on aclanthology. The online version of the hybrid poster session will be on GatherTown. If you access the ACL underline and find the WASSA page, you should have links to both Zoom and GatherTown. If you have any problems, let us know.
June 19: The schedule for WASSA 2023 is now up.
May 25: David Jurgens has confirmed that he will be an invited speaker as well.
May 1: WASSA 2023 submissions will need to upload prerecorded videos and slides on Underline, following the process of the main conference. The hard deadline for uploading is June 12, 2023. We will include further information regarding where to submit these in the future, but please take this into account when planning your presentations.
April 25: Emily Öhman has confirmed that she will be one of the invited speakers.
April 19: We have extended the submission deadline to April 28th (see Important Dates for further details of changes)
February 15: The date of WASSA 2023 is confirmed to be the 14th of July.
January 13: The OpenReview Workshop Portal is up.
Invited Speakers
Emily Öhman: Waseda University
David Jurgens: University of Michigan
Background and Envisaged Scope
Subjectivity and Sentiment Analysis has become a highly developed research area, ranging from binary classification of reviews to the detection of complex emotion structures between entities found in text. This field has expanded both on a practical level, finding numerous successful applications in business, as well as on a theoretical level, allowing researchers to explore more complex research questions related to affective computing. Its continuing importance is also shown by the interest it generates in other disciplines such as Economics, Sociology, Psychology, Marketing, Crisis Management & Digital Humanities.
The aim of WASSA 2023 is to bring together researchers working on Subjectivity, Sentiment Analysis, Emotion Detection and Classification and their applications to other NLP or real-world tasks (e.g. public health messaging, fake news, media impact analysis, social media mining, computational literary studies) and researchers working on interdisciplinary aspects of affect computation from text. For this edition, we encourage the submission of long and short research and demo papers including, but not restricted to the following topics:
- Resources for subjectivity, sentiment, emotion and social media analysis
- Opinion retrieval, extraction, categorization, aggregation and summarization
- Humor, Irony and Sarcasm detection
- Mis- and disinformation analysis and the role of affective attributes
- Aspect and topic-based sentiment and emotion analysis
- Analysis of stable traits of social media users, incl. personality analysis and profiling
- Transfer learning for domain, language and genre portability of sentiment analysis
- Modelling commonsense knowledge for subjectivity, sentiment or emotion analysis
- Improvement of NLP tasks using subjectivity and/or sentiment analysis
- Intrinsic and extrinsic evaluation of subjectivity and/or sentiment analysis
- The role of emotions in argument mining
- Application of theories from related fields to subjectivity and sentiment analysis
- Multimodal emotion detection and classification
- Applications of sentiment and emotion mining
- Public sentiments and communication patterns of public health emergencies.
We furthermore encourage submissions to the special theme Ethics in Affective Computing, including opinion papers, as well as experimental papers. This includes the following topics, but is not limited to them:
- Which properties of a model render a automatic analysis task unethical?
- Which characteristics of an annotation task are to be considered in ethical considerations?
- What are appropriate methods to analyze data and models from an ethical perspective?
- What aspects are particular important for affective analysis tasks, in contrast to other NLP settings?
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