Capitalizing on Rumors in Social Media

Using social media as a source of breaking news has many advantages, but one that made itself readily apparent on Sunday was the ability to react to rumors. Whereas traditional news channels tend to focus on substantiated, double- and triple-fact-checked stories that are generated from official press conferences and earning reports, social media presents no such restrictions to its users. Twitter has the ability to broadcast tons of information to an extremely wide audience. In addition to being an outlet for established news sources, both professional and amateur analysts have the ability to speak whatever is on their mind. Nothing is automatically filtered and there are only minor regulations on content. While relying on unsubstantiated data can obviously be a double-edged sword, being able to process early fragments of information and make sense of them can be a huge advantage in analyzing how the market will react to breaking news.

Early Sunday evening, rumors began to swirl on Twitter that IBM was planning a massive reorganization that would result in laying off anywhere from 100,000 to 112,000 employees.

This is obviously shocking news, and if it came from an isolated, untrusted user it could almost be dismissed out of hand. However, several tweets started to become a trend. The Social Alpha analytics engine began to notice that these rumors were coming from reliable, influential sources, and social market sentiment indicators started to drop, indicating a “Bearish” outlook.

IBM social sentiment begins to drop as layoff rumors start to spread on Twitter

While this trend started around 5:30 PM on Sunday evening and quickly picked up steam on social media, the market was slower to react. The story wasn’t yet heavily reported through traditional news sources, and on a day when the market as a whole opened down, IBM’s stock opened up 2.2%. As the rumors proliferated, the stock began to mirror the trend in social sentiment and fell steadily throughout the day, losing almost all of its opening gains as it closed up only 0.3% for the day.

After a bullish open, the market catches on to the bad news and the stock slides 2% throughout the day

While lots of information about IBM is broadcast each day, in this case Social Alpha was able to identify noteworthy tweets that would have a future impact on the market, filter out the ones that weren’t important, and produce a sentiment indicator that correctly predicted the next day’s movements. This in turn presented a good opportunity: while the rest of the market was still bullish, paying attention to the social indicators on the night before the market opened would have allowed an investor to adopt a bearish outlook before everyone else adjusted.

Paying attention to rumors can be dangerous. It’s still not certain how much truth is in the IBM story, and taking everything you read on Twitter as fact is certainly not prudent. But being able to accurately filter and interpret data from all sources — particularly social media where the challenge is greatest — can present great opportunities for investment in a fast-evolving market.