Monday, October 24, 2011

#ALGORITHMS: "Social Analytics Tracks Baseball Sentiments"

The Annenberg Social Sentiment Index--powered by IBM Social Analytics--is measuring fans' feelings from analytics that scan millions of baseball World Series tweets.

Retargeting analytics from pure business decision-support to tracking social sentiments in the more fun aspects of life--such as the ongoing baseball World Series--is the goal of a new social sentiment index created by the University of Southern California. The USC Annenberg Innovation Lab will present its baseball analytics project at the 2011 IBM Information on Demand and Business Analytics Forum (this week in Las Vegas).
The project's aim is to show how the same analytics that IBM's Watson used to beat human champions in the TV game show "Jeopardy," could be repurposed for interesting social media data mining. Analytics included both semantic and linguistic analysis of real-time posts on Twitter. Past social-sentiments projects by the Annenberg Innovation Lab include journalistic-oriented analytics applied to news stories, movie-oriented analytics predicting successes from film critiques, and retail-oriented analytics identifying trends in fashion shows.
IBM has had a long interest in baseball, as evidenced here in a picture of their team in 1938. (Source: IBM)
The Social Sentiment Index offers a "unique opportunity to gain valuable knowledge in the use of advanced analytics technologies [applied] to real-world settings to understand how this new information can benefit a variety of industries," said professor Jonathan Taplin, director of the USC Annenberg Innovation Lab.
Baseball analytics was recently featured in a major book and film--"Moneyball"--which describes how "big data" analytics was instrumental in the decisions made by Oakland Athletics general manager Billy Beane. And some baseball experts have suggested that the same “Moneyball” approach to selecting players and assembling a team is what got the Rangers and the Cardinals to the World Series over teams with higher payrolls.
"Organizations are realizing the value of analytics to better respond to customer needs, whether it’s analyzing fan sentiment during a sports event, hospital patient data for personalized treatment programs or the latest fashion trends for more targeted marketing campaigns," said Rod Smith, vice president of emerging technology, IBM.
During the World Series, fans are being encouraged to use the Twitter hash-tag "#postseason" which simplifies the accumulation of tweets for analysis. Compiled by USC students using IBM Social Analytics technology, over a million tweets have already been analyzed during the National League Championship Series (NLCS). This work has now been broadened for the World Series.
IBM Social Analytics is a relatively new feature in IBM Connections, which is available for compatible Home Pages, Communities and Profile pages. A "Recommendations" widget suggests content that users might find interesting and related communities they might want to join. The "Do You Know" widget recommends people to add to a social network, the "Things in Common" widget identifies others with common interests, and the "Who Connects Us" widget traces the social "path" that connects users.
So far, Annenberg's Social Sentiment Index has found that the St. Louis Cardinals' Chris Carpenter is the most popular player (with 1,573 tweets 61 percent of which were positive). Cardinal David Freeze came in second (768 tweets, 89 percent of which were positive). Overall, however, the Texas Rangers is the most popular team (over 56,000 tweets, 79 percent of which were positive) with five times as many tweets as the Cardinals (11,500 tweets, 80 percent of which were positive).
Further Reading