You are here

SemEval-2017 Task 5: Fine-Grained Sentiment Analysis on Financial Microblogs and News


Keith Cortis, Andre Freitas, Tobias Daudert, Manuela Huerlimann, Manel Zarrouk, Andre Freitas, Brian Davis

Publication Type: 
Refereed Conference Meeting Proceeding
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.
Conference Name: 
11th International Workshop on Semantic Evaluations (SemEval-2017)
Digital Object Identifer (DOI): 
Publication Date: 
Conference Location: 
Research Group: 
National University of Ireland, Galway (NUIG)
Open access repository: