Can Social Media Predict the Stock Market?

In 2018, Elon Musk tweeted that he was “considering taking Tesla private at $420” and claimed “funding secured”. Within minutes, Tesla’s stock price surged 11%. In the same year, Kylie Jenner posted her discontent with snapchat, saying how “it’s so sad” that no one uses it anymore. This simple message led to snapchats market falling by about $1.3 Billion the next day. A fake tweet claiming that Steve Jobs had died sent Apple’s stock dropping by 5.4%. And more recently, Tesla’s shares dropped 14% following a very public feud between Donald Trump and Musk on the internet, causing investors to lose confidence in the short run. 

These aren’t just isolated cases, they’re part of a larger reality that in the world of finance, nothing moves faster than information. And social media is the biggest delivery vehicle of it all. Platforms like X, Instagram, Reddit, Discord are becoming increasingly popular amongst retail investors and this is causing us to shift to a very sentiment and emotion driven volatile market. 

The price of a stock is ultimately driven by its supply and demand. Supply is relatively constant, however demand can change instantly when new information, or perception of it- enters the public sphere. The Efficient Market Hypothesis states that all publicly available information is immediately reflected in stock prices. In our era, publicly available can mean a tweety, a meme, or even a viral rumour. Behavioral economics adds an important layer that people are not perfectly rational. Studies have shown that negative social media posts have a significantly stronger effect on stock returns than positive posts. This ties into loss aversion theory that suggests that people fear losses more than they value equivalent gains. A single negative post can trigger disproportionately large sell offs.

Social platforms amplify confirmation bias through echo chambers. Bullish investors follow bullish accounts and are shown bullish posts that reinforce their optimism, while bearish investors are surrounded with pessimism. This selective exposure fuels herding behaviour, which is the tendency to follow what the majority appears to be doing, often without independent analysis. In finance, this manifests as FOMO (Fear of Missing Out) where people simply buy because “everyone else” seems to be buying. A notable parallel is the 2014 Facebook experiment that showed how changing the emotional tone of a news feed influences the mood of users. In investing terms, a news feed full of luxury lifestyles and “success stories” can lead traders to make riskier trades, subconsciously trying to emulate what they perceive as the behaviours of the wealthy.

Another bizarre yet major example of social media’s influence on the stock market is the GameStop saga in January 2021. GameStop was a dying video game retailer which had Wall Street investors and hedge funds betting heavily on its failure. Now, users on a particular reddit forum noticed that hedge fund investors were seriously hoping for GameStop’s shares to fall so that the investors could re-buy it at a cheaper price. These users then collectively decided to buy the stock in huge numbers to drive up its price, forcing a “short squeeze”, making the price rocket almost 2000%. Hedge funds and investors had to immediately sell all shares to make sure the prices don’t further skyrocket. This frenzy was fueled by memes, hype, and a sense of rebellion that spread faster than any traditional news media. This episode showed, in the clearest and strangest way, how social media can turn an online movement into a force capable of shaking the stock market itself.

While regression models have found statistically meaningful relationships between social media sentiment and stock price movements, predicting the precise short term effect remains elusive. The speed and virality that give social media its market-moving power make it chaotic and unpredictable. Thus ultimately, predicting unpredictability is problematic and it’s best to focus on company fundamentals for the long term- because tweets don’t last forever, strong businesses do.