@inproceedings{mansar-etal-2017-fortia,
title = "Fortia-{FBK} at {S}em{E}val-2017 Task 5: Bullish or Bearish? Inferring Sentiment towards Brands from Financial News Headlines",
author = "Mansar, Youness and
Gatti, Lorenzo and
Ferradans, Sira and
Guerini, Marco and
Staiano, Jacopo",
editor = "Bethard, Steven and
Carpuat, Marine and
Apidianaki, Marianna and
Mohammad, Saif M. and
Cer, Daniel and
Jurgens, David",
booktitle = "Proceedings of the 11th International Workshop on Semantic Evaluation ({S}em{E}val-2017)",
month = aug,
year = "2017",
address = "Vancouver, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S17-2138",
doi = "10.18653/v1/S17-2138",
pages = "817--822",
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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%0 Conference Proceedings
%T Fortia-FBK at SemEval-2017 Task 5: Bullish or Bearish? Inferring Sentiment towards Brands from Financial News Headlines
%A Mansar, Youness
%A Gatti, Lorenzo
%A Ferradans, Sira
%A Guerini, Marco
%A Staiano, Jacopo
%Y Bethard, Steven
%Y Carpuat, Marine
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%Y Cer, Daniel
%Y Jurgens, David
%S Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
%D 2017
%8 August
%I Association for Computational Linguistics
%C Vancouver, Canada
%F mansar-etal-2017-fortia
%X 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.
%R 10.18653/v1/S17-2138
%U https://aclanthology.org/S17-2138
%U https://doi.org/10.18653/v1/S17-2138
%P 817-822
Markdown (Informal)
[Fortia-FBK at SemEval-2017 Task 5: Bullish or Bearish? Inferring Sentiment towards Brands from Financial News Headlines](https://aclanthology.org/S17-2138) (Mansar et al., SemEval 2017)
ACL