Quantifying the impacts of online fake news on the equity value of social media platforms – Evidence from Twitter

作者：

Highlights：

• Identifies Falsehood and Ambiguity as two defining characteristics of online fake news.

• Synthesizes the literature on negativity bias and platform failure to frame five hypotheses.

• Designs and implements a two-stage Bayesian Vector Autoregression to test the mechanisms.

• Falsehood causes a 2.11 Million USD loss in equity value over a ten-day period.

• Falsehood and Ambiguity interact to produce a 10 Million USD loss in equity value.

摘要

•Identifies Falsehood and Ambiguity as two defining characteristics of online fake news.•Synthesizes the literature on negativity bias and platform failure to frame five hypotheses.•Designs and implements a two-stage Bayesian Vector Autoregression to test the mechanisms.•Falsehood causes a 2.11 Million USD loss in equity value over a ten-day period.•Falsehood and Ambiguity interact to produce a 10 Million USD loss in equity value.

论文关键词：Fake News,Social media,Equity value,Falsehood,Ambiguity,Vector auto regression and bayesian statistics

论文评审过程：Received 27 February 2021, Revised 16 January 2022, Accepted 17 January 2022, Available online 25 January 2022, Version of Record 25 January 2022.

论文官网地址：https://doi.org/10.1016/j.ijinfomgt.2022.102474