Work

FinSentiA: Sentiment Analysis in English Financial Microblogs

Year: 2018

Type: conference-paper

Abstract: The objective of this paper is to report on the building of a Sentiment Analysis (SA) system dedicated to financial microblogs in English. The purpose of our work is to build a financial classifier that predicts the sentiment of stock investors in microblog platforms such as StockTwits and Twitter. Our contribution shows that it is possible to conduct such tasks in order to provide fine-grained SA of financial microblogs. We extracted financial entities with relevant contexts and assigned scores on a continuous scale by adopting a deep learning method for the classification. Results show a 0.85 F1-Score on a two-class basis and a 0.62 cosine similarity score.

Source: Arrow@dit (Dublin Institute of Technology)

DOI: 10.13025/s8xp7d

Authors: Gaillat, Thomas, Sousa, Annanda, Zarrouk, Manel, Davis, Brian

Institutions: Université Rennes 2, Linguistique Ingénierie et Didactique des Langues, University College Cork, Insight SFI Research Centre for Data Analytics, Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier, National University of Ireland, Maynooth

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2913665143

FWCI: 0.511

Cites: 23

Cited by: 5

Related to: 10