SemEval-2017 Task 5: Fine-grained sentiment analysis on financial microblogs and news
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Date
2017-08-03Author
Cortis, Keith
Freitas, André
Daudert, Tobias
Huerlimann, Manuela
Zarrouk, Manel
Handschuh, Siegfried
Davis, Brian
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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.
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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.