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.

The post Capitalizing on Rumors in Social Media appeared first on Social Alpha.

But even before the markets opened, the more than usual social chatter around Apple on Twitter forecasted the upcoming volatility in the price of AAPL. The Apple stock continues to be a social media sweetheart, with more than 3,000 tweets about it on regular days. But on the morning of September 9th, there was an unusual uptick in social buzz around AAPL, leading up to a staggering 13,000 messages on Twitter about the stock, just within a 6-hour period. Intelligent anomaly-detection algorithms were able to detect this unusual trend early on; and half an hour before the market opened, messages were sent out alerting investors to the rocky day ahead for Apple.

Sophisticated Computational Linguistic techniques are able to rapidly assess the opinions of thousands of analysts and investors in the matter of nanoseconds, and thus gauge the social pulse of the market. This social market-sentiment tends to be a leading indicator of stock price movements. The significant rise and fall of sentiment around AAPL was clearly reflected in the price 6 hours later.

The post How Twitter Predicted Apple Stock Movement Before Its Product Announcements appeared first on Social Alpha.