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Old Age
Fortia-FBK at SemEval-2017 Task 5: Bullish or Bearish? Inferring Sentiment towards Brands from Financial News Headlines
April 04, 2017 ยท Declared Dead ยท ๐ International Workshop on Semantic Evaluation
"No code URL or promise found in abstract"
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Authors
Youness Mansar, Lorenzo Gatti, Sira Ferradans, Marco Guerini, Jacopo Staiano
arXiv ID
1704.00939
Category
cs.CL: Computation & Language
Cross-listed
cs.CY
Citations
26
Venue
International Workshop on Semantic Evaluation
Last Checked
4 months ago
Abstract
In this paper, we describe a methodology to infer Bullish or Bearish sentiment towards companies/brands. More specifically, our approach leverages affective lexica and word embeddings in combination with convolutional neural networks to infer the sentiment of financial news headlines towards a target company. Such architecture was used and evaluated in the context of the SemEval 2017 challenge (task 5, subtask 2), in which it obtained the best performance.
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