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SardiStance @ EVALITA2020: Overview of the Task on Stance Detection in Italian Tweets

Contributo in Atti di convegno
Data di Pubblicazione:
2020
Abstract:
SardiStance is the first shared task for Italian on the automatic classification of stance in tweets. It is articulated in two different settings: A) Textual Stance Detection, exploiting only the information provided by the tweet, and B) Contextual Stance Detection, with the addition of information on the tweet itself such as the number of retweets, the number of favours or the date of posting; contextual information about the author, such as follower count, location, user's biography; and additional knowledge extracted from the user's network of friends, followers, retweets, quotes and replies. The task has been one of the most participated at EVALITA 2020 (Basile et al., 2020), with a total of 22 submitted runs for Task A, and 13 for Task B, and 12 different participating teams from both academia and industry. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
Tipologia CRIS:
04A-Conference paper in volume
Elenco autori:
Alessandra Teresa Cignarella, Mirko Lai, Cristina Bosco, Viviana Patti, Paolo Rosso
Autori di Ateneo:
BOSCO Cristina
PATTI Viviana
Link alla scheda completa:
https://iris.unito.it/handle/2318/1764607
Link al Full Text:
https://iris.unito.it/retrieve/handle/2318/1764607/687061/paper159.pdf
Titolo del libro:
Proceedings of the Seventh Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop (EVALITA 2020)
Pubblicato in:
CEUR WORKSHOP PROCEEDINGS
Journal
CEUR WORKSHOP PROCEEDINGS
Series
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URL

ceur-ws.org/Vol-2765/paper159.pdf
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