Fact Check: Analyzing Financial Events from Multilingual News Sources
- URL: http://arxiv.org/abs/2106.15221v3
- Date: Fri, 25 Aug 2023 12:40:07 GMT
- Title: Fact Check: Analyzing Financial Events from Multilingual News Sources
- Authors: Linyi Yang, Tin Lok James Ng, Barry Smyth, Ruihai Dong
- Abstract summary: We propose FactCheck in finance, a web-based news aggregator with deep learning models.
A web interface is provided to examine the credibility of news articles using a transformer-based fact-checker.
The performance of the fact checker is evaluated using a dataset related to merger and acquisition (M&A) events.
- Score: 22.504723681328507
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The explosion in the sheer magnitude and complexity of financial news data in
recent years makes it increasingly challenging for investment analysts to
extract valuable insights and perform analysis. We propose FactCheck in
finance, a web-based news aggregator with deep learning models, to provide
analysts with a holistic view of important financial events from multilingual
news sources and extract events using an unsupervised clustering method. A web
interface is provided to examine the credibility of news articles using a
transformer-based fact-checker. The performance of the fact checker is
evaluated using a dataset related to merger and acquisition (M\&A) events and
is shown to outperform several strong baselines.
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