Computing the Veracity of Information Through Crowds: A Method for Reducing the Spread of False Messages on Social Media

11 Pages Posted: 14 Feb 2015 Last revised: 11 Sep 2015

See all articles by Huaye Li

Huaye Li

Stevens Institute of Technology - School of Business

Yasuaki Sakamoto

AXA Direct Japan

Date Written: February 12, 2015

Abstract

Twitter and other social media allow people to post their experiences and opinions online. This information can be useful for making informed decisions. However, people can unintentionally spread false information. The work reported here focused on examining how to reduce the spread of inaccurate information on social media. In particular, we examined the effect of collective opinion on information forwarding in social media environments through an experiment with crowds. In Twitter, an indicator of collective opinion is the number of people who have retweeted a message. The results showed that displaying both retweet counts and collective truthfulness ratings could reduce the spread of inaccurate health-related messages. This finding suggests that collecting and displaying the truthfulness ratings of crowds in addition to their forwarding decisions can reduce the spread of false information on social media.

Suggested Citation

Li, Huaye and Sakamoto, Yasuaki, Computing the Veracity of Information Through Crowds: A Method for Reducing the Spread of False Messages on Social Media (February 12, 2015). Stevens Institute of Technology School of Business Research Paper No. 2015-43. Available at SSRN: https://ssrn.com/abstract=2564247 or http://dx.doi.org/10.2139/ssrn.2564247

Huaye Li (Contact Author)

Stevens Institute of Technology - School of Business ( email )

Hoboken, NJ 07030
United States

Yasuaki Sakamoto

AXA Direct Japan ( email )

Japan

Register to save articles to
your library

Register

Paper statistics

Downloads
63
Abstract Views
420
rank
348,528
PlumX Metrics