Reality Buzz
John T. Maloney (jheuristic)
social media conversations could predict the outcome of popular shows…
The Power of Social Media Data in Business
Article | 06.22.10 | By Stefan Andreasen
With just about every major brand and celebrity on Facebook and Twitter, the
line between social media and popular culture is becoming harder to
distinguish by the day. What is evident is the incredible power social media
has in uncovering popular sentiment and the way information is being shared
and disseminated. The sheer amount of data amassed on any social network on
any given day holds an incredible amount of intelligence and insight into
where the collective sentiment of the masses lies.
The numbers speak for themselves: Twitter grew 1,444 percent last year with
more than 50 million tweets sent each day, and Facebook now has over 400
million active users. Every minute, 600 new blog posts are published, 34,000
tweets are sent, and 240,000 pieces of content are shared on Facebook.
The question now is how businesses can benefit from all this data and what,
if any, tangible intelligence can be extracted from it.
In fact, the aggregation of data from social media networks and forums can
become an incredibly powerful tool for gathering real-time intelligence and
making more informed and strategic business decisions. Companies can also
analyze the data to better understand customer sentiment and satisfaction,
market trends and competitive threats, to name just a few. From a cultural
standpoint, the data can also provide insight into the collective opinions
of the masses on a number of relevant issues, including political elections,
social crises (like the BP oil spill) and yes, even reality television
shows.
Case in point: At Kapow Technologies we created Reality Buzz, a social media
analysis project that examined whether real-time analysis of social media
conversations could predict the outcome of popular shows like American
Idol and Dancing with the Stars. Reality Buzz semantically extracted tens of
thousands of tweets, comments and discussions about contestants on both
programs each week and applied sentiment analysis to the data. In the end,
we were able to draw some clear, data-driven conclusions to predict the
contestants who would be eliminated each week.
Continue here…
http://www.semanticuniverse.com/articles-power-social-media-data-business.ht
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