SemEval-2018 Task 1: Affect in tweets

From National Research Council Canada

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DOI	Resolve DOI: https://doi.org/10.18653/v1/S18-1001
Author	Search for: Mohammad, Saif¹; Search for: Bravo-Marquez, Felipe; Search for: Salameh, Mohammad; Search for: Kiritchenko, Svetlana¹
Name affiliation	National Research Council of Canada. Digital Technologies
Format	Text, Article
Proceedings title	Proceedings of The 12th International Workshop on Semantic Evaluation
Conference	International Workshop on Semantic Evaluation (SemEval-2018), June 2018, New Orleans, Louisiana, USA
Pages	1–17
Abstract	We present the SemEval-2018 Task 1: Affect in Tweets, which includes an array of subtasks on inferring the affectual state of a person from their tweet. For each task, we created labeled data from English, Arabic, and Spanish tweets. The individual tasks are: 1. emotion intensity regression, 2. emotion intensity ordinal classification, 3. valence (sentiment) regression, 4. valence ordinal classification, and 5. emotion classification. Seventy-five teams (about 200 team members) participated in the shared task. We summarize the methods, resources, and tools used by the participating teams, with a focus on the techniques and resources that are particularly useful. We also analyze systems for consistent bias towards a particular race or gender. The data is made freely available to further improve our understanding of how people convey emotions through language.
Publication date	2018
Publisher	Association for Computational Linguistics
Place	Stroudsburg, PA, USA
Licence	Creative Commons, Attribution 4.0 Generic (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/
Language	English
Peer reviewed	Yes
NPARC number	23003178
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Record identifier	560b602a-37a5-47be-b306-4b80277382ea
Record created	2018-05-04
Record modified	2020-11-27

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Date modified:: 2021-04-22