Characterizing Fake News Targeting Corporations

TL;DR

This paper provides a large-scale, data-driven characterization of corporate misinformation targeting S&P 500 companies by integrating Reddit discussions, domain credibility, stock performance, and Glassdoor sentiment. It develops a two-level taxonomy for fake-news articles, validated via crowd-sourced annotation during misinformation shocks, and shows that targeted firms tend to attract reputable coverage but receive less social-media attention, with negative sentiment and lower stock growth accompanying misinformation events. Cross-lagged analyses reveal temporal dynamics among stock valuation, external reputation, internal stress, and fake-news exposure, indicating that shocks cluster in concentrated periods and can influence subsequent outcomes. The work offers practical implications for regulators, executives, and investors, advocating continuous monitoring, timely crisis communication, and a nuanced understanding of how different misinformation categories affect firms internally and externally.

Abstract

Misinformation proliferates in the online sphere, with evident impacts on the political and social realms, influencing democratic discourse and posing risks to public health and safety. The corporate world is also a prime target for fake news dissemination. While recent studies have attempted to characterize corporate misinformation and its effects on companies, their findings often suffer from limitations due to qualitative or narrative approaches and a narrow focus on specific industries. To address this gap, we conducted an analysis utilizing social media quantitative methods and crowd-sourcing studies to investigate corporate misinformation across a diverse array of industries within the S\&P 500 companies. Our study reveals that corporate misinformation encompasses topics such as products, politics, and societal issues. We discovered companies affected by fake news also get reputable news coverage but less social media attention, leading to heightened negativity in social media comments, diminished stock growth, and increased stress mentions among employee reviews. Additionally, we observe that a company is not targeted by fake news all the time, but there are particular times when a critical mass of fake news emerges. These findings hold significant implications for regulators, business leaders, and investors, emphasizing the necessity to vigilantly monitor the escalating phenomenon of corporate misinformation.

Figures (6)

• Figure 1: Reddit users versus U.S. state population.
• Figure 2: Monthly # of Reddit comments containing both a fake link and a company name (median: 408, standard deviation: 136). The peaks observed in early 2017 and late 2018 were mainly caused by news about Google and Facebook. They were accused of not complying with the law that requests the removal of harmful content (Facebook) and using politically biased algorithms (Google).
• Figure 3: Moral dimensions along which our participants judged a company mentioned in news articles.
• Figure 4: Bipartite graph connecting companies (left hand side) with the fake news outlets (right hand side) mentioning them. A company that is likely to be target by fake news tends to be a tech company such as Facebook and Apple. Tech companies tend to be targeted by multiple outlets, while communication ones (e.g., Google) tend to be targeted by specific outlets such as stonecoldtruth.com.
• Figure 5: Fake news shocks (peaks of $pFake(C, T_{month})$ over time, shown with the gray bars) for a company C that: is a Tech company (Apple and Google); is a Communication company (Facebook); has not done well in the stock market (General Electric); attracts considerable negative mentions on social media (JPMorgan); and attracts considerable stress mentions by its employees (Disney).