We examine the determinants and market consequences associated with earnings announcements going viral on social media, a phenomenon we label “earnings virality.” Using a comprehensive panel of historical Twitter data, we find that the typical earnings announcement receives relatively little social media coverage, but others go viral on social media, quickly reaching the feeds of millions of people. We find that viral earnings announcements generally have Twitter content that is more extreme in tone and contains less unique content. Further, earnings virality is positively associated with revenue surprises, investor recognition, retail investor ownership, and retail investor trading around the announcement. Earnings virality appears to be detrimental to markets, as it coincides with lower market liquidity and slower price formation. Overall, our evidence suggests that user-driven dissemination through social media platforms, when amplified and taken to extreme levels, may be harmful to markets.
We investigate whether economic narratives in religious sermons influence household economic decisions. Leveraging geographic variation in membership density of The Church of Jesus Christ of Latter-day Saints, we examine whether regions with more Church members exhibit less indebtedness when Church leaders speak about debt avoidance in worldwide religious broadcasts. We show that the household debt-to-income ratio is lower in regions with more Church members during years with debt-avoidance sermons, and several additional analyses corroborate our conclusions. Our models suggest that this effect is economically meaningful, emphasizing the importance of considering narratives alongside traditional determinants when studying economic decisions and outcomes.
I examine the capital market impact of fake social media accounts, commonly known as bots. Using a large sample of X (Twitter) data, I examine whether investors are aware of the presence of bots and can detect them. The results suggest that investors have difficulty distinguishing bots from real accounts. However, they appear to be aware of the probability of misinformation and adjust their beliefs accordingly. I find that bot activity is associated with positive contemporaneous returns followed by reversals as well as less informed retail trading. I also observe evidence of a disciplining role of accounting information. The impact of fake accounts appears to weaken after the release of accounting earnings, and reversals following bot activity appear to be concentrated around the release of accounting earnings. Finally, I leverage a plausibly exogenous shock where Twitter suspended many bots over a short period. The results are consistent with bots affecting investors’ trading decisions.