Using Multi-View Learning to Improve Detection of Investor Sentiments on Twitter

Authors

  • Zvi Ben-Ami The Hebrew University, School of Business Administration
  • Ronen Feldman Digital Trowel
  • Binyamin Rosenfeld Digital Trowel

DOI:

https://doi.org/10.13053/cys-18-3-2019

Keywords:

Sentiment analysis, Sentiment expression mining, unsupervised learning, Multi-view learning, Investors sentiments, Social media.

Abstract

Stocks-related messages on social media have several interesting properties regarding the sentiment analysis (SA) task. On the one hand, the analysis is particularly challenging, because of frequent typos, bad grammar, and idiosyncratic expressions specific to the domain and media. On the other hand, stocks-related messages primarily refer to the state of specific entities – companies and their stocks, at specific times (of sending). This state is an objective property and even has a measurable numeric characteristic, namely the stock price. Given a large dataset of twitter messages, we can create two separate "views" on the dataset by analyzing messages’ text and external properties separately. With this, we can expand the coverage of generic SA tools and learn new sentiment expressions. In this paper, we experiment with this learning method, comparing several types of general SA tools and sets of external properties. The method is shown to produce significant improvement in accuracy.

Author Biographies

Zvi Ben-Ami, The Hebrew University, School of Business Administration

Zvi Ben-Ami is a Doctoral candidate at the School of Business Administration of the Hebrew University of Jerusalem. He received his B.A in Insurance form Netanya Academic College in 2000 and his M.Com in Business Management form University of Port Elizabeth in 2004.

Ronen Feldman, Digital Trowel

Ronen Feldman is an Associate Professor of Information Systems at the Business School of the Hebrew University in Jerusalem. He received his B.Sc. in Math, Physics and Computer Science from the Hebrew University in 1984 and his Ph.D. in Computer Science from Cornell University in NY in 1993.

Binyamin Rosenfeld, Digital Trowel

Binyamin Rosenfeld is a research scientist at Digital Trowel. He received his B.Sc. in Mathematics and Computer Science from Bar-Ilan University in 1998.

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Published

2014-09-29

Issue

Vol. 18 No. 3 (2014): 18(3) 2014 Thematic issue: Computational linguistics (Guest editor: Alexander Gelbukh)

Section

Articles

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