SemEval-2017 Task 5: Fine-grained sentiment analysis on financial microblogs and news
Cortis, Keith Freitas, André Daudert, Tobias Huerlimann, Manuela Zarrouk, Manel Handschuh, Siegfried Davis, Brian
Cortis, Keith
Freitas, André
Daudert, Tobias
Huerlimann, Manuela
Zarrouk, Manel
Handschuh, Siegfried
Davis, Brian
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Repository DOI
Publication Date
2017-08-03
Type
Conference Paper
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Citation
Cortis, Keith, Freitas, André , Daudert, Tobias , Huerlimann, Manuela , Zarrouk, Manel , Freitas, André, & Davis, Brian (2017). SemEval-2017 Task 5: Fine-Grained Sentiment Analysis on Financial Microblogs and News. Paper presented at the 11th International Workshop on Semantic Evaluations (SemEval-2017), Vancouver, Canada.
Abstract
This paper discusses the “Fine-Grained Sentiment Analysis on Financial Microblogs and News” task as part of SemEval-2017, specifically under the “Detecting sentiment, humour, and truth” theme. This task contains two tracks, where the first one concerns Microblog messages and the second one covers News Statements and Headlines. The main goal behind both tracks was to predict the sentiment score for each of the mentioned companies/stocks. The sentiment scores for each text instance adopted floating point values in the range of -1 (very negative/bearish) to 1 (very positive/bullish), with 0 designating neutral sentiment. This task attracted a total of 32 participants, with 25 participating in Track 1 and 29 in Track 2.
Funder
Publisher
Association for Computational Linguistics
Publisher DOI
10.18653/v1/S17-2089
Rights
Attribution-NonCommercial-NoDerivs 3.0 Ireland