Just as the New York Giants rallied late in the fourth quarter on Sunday to defeat the New England Patriots in the Super Bowl for the second time in 4 years, IBM and the University of Southern California Annenberg Innovation Lab teamed up last week to determine fans' favorite quarterback leading up to Super Bowl XLVI: Tom Brady or Eli Manning. Researchers examined data from Twitter using new analytics technologies that can understand positive, negative and neutral sentiments, distinguish irony, and utilize "machine learning" to separate important tweets from trivial ones.
The results, which were published on the Thursday before the game, indicated a virtual tie between the signal callers, with Tom Brady receiving 65% positive sentiment and Eli Manning close behind with 62% positive sentiment. This was considered, however, somewhat of an upset, as Tom Brady was expected to beat Eli Manning handily (as favorite quarterback) due to his long tenure as an elite quarterback and his three Super Bowl championships.
Analyzing data from social media is a new and growing technique among businesses to gain greater insight into how customers perceive and interact with their brand. Rod Smith, vice president of emerging technologies at IBM, tells 5 Minute Briefing, "The business applicability will continue to grow but it's really at its infancy right now." Currently, businesses face challenges in deriving value from this nascent technology. "The part that is daunting for businesses is the ‘needle in the haystack,'" suggests Smith. "People produce on Twitter 7-8 terabytes of data a day, and if you're in a particular business, maybe a tenth of a percent or less is interesting to you." This has not, however, stopped organizations from mining social media data for valuable business intelligence.
The emergence of social media data analysis is influencing organizations across many departments, from IT to marketing, as well as the relationship between the organization and its customers. Social media empowers customers to shape and influence the perceptions of a business, while also opening new avenues of interaction. Smith states, "Businesses are realizing that this is a unique way that they can interact unencumbered" with customers.
There is little debate that social media data analysis is a powerful and growing technology that can improve the bottom line of virtually any business. However, organizations' business departments are finding value in social media data, IT departments are still struggling to leverage this data. Smith concedes, "IT departments aren't necessarily quite sure what to do with it." Social media data analysis is still a very young technology that, Smith believes, will have a bright future in the IT sector. "I think over time as we understand those business cases and use cases more, we'll be able to help people bring that back into IT and understand the technologies and how they integrate into their data warehouses."
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