Predicting the Future with Social Media

Abstract

In recent years, social media has become ubiquitous and important for social networking and content sharing. And yet, the content that is generated from these websites remains largely untapped. In this paper, we demonstrate how social media content can be used to predict real-world outcomes. In particular, we use the chatter from Twitter.com to forecast box-office revenues for movies. We show that a simple model built from the rate at which tweets are created about particular topics can outperform market-based predictors. We further demonstrate how sentiments extracted from Twitter can be further utilized to improve the forecasting power of social media.

References in corpus (2)

• Twitter mood predicts the stock market
• Web search queries can predict stock market volumes

Cited by in corpus (9)

• Twitter mood predicts the stock market
• Detecting and Tracking the Spread of Astroturf Memes in Microblog Streams
• Web search queries can predict stock market volumes
• Can social microblogging be used to forecast intraday exchange rates?
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• Forecasting of Events by Tweet Data Mining
• S-MART: Novel Tree-based Structured Learning Algorithms Applied to Tweet Entity Linking
• Why Watching Movie Tweets Won't Tell the Whole Story?
• Data Mining of the Concept "End of the World" in Twitter Microblogs