For over 80 years, professional pollsters have been trying to predict election outcomes. Now, an unlikely new technology may bring them one step closer to predicting the next President of the United States: social media.

 A new study released today by OhMyGov Research – the media analytics arm of OhMyGov Inc. – showed a strong association between a politician’s popularity on social media and political polling numbers.

 The study analyzed whether Facebook and Twitter fan and follower numbers and account growth rates correlate with political polling data by examining the leading Republican presidential candidates over a six-month period.  Results from the study showed a statistically significant correlation between the total number of social media Facebook fans and Twitter followers a candidate had and his/her popularity in the polls.

 Over the past six months leading up to the upcoming 2012 Republican primaries, many voters have been seeing campaign messages, debates, and political commentary —not only through traditional media, but also on social networking sites like Twitter and Facebook. Voters react instantly to the candidates' appearance, words and policies on such platforms. But do reactions on social media mirror reality? This study certainly suggests it does, especially on Facebook, where the correlation between fans (“likes”) and polling numbers was even stronger than that between Twitter followers and polling data.

 “Federal, state and local elections are all using social media to engage voters and the media, so it’s no surprise to me that we found a correlation between social data and polling,” said Andrew B. Einhorn, CEO of OhMyGov Inc. “We saw similar results in our 2010 study of Congressional elections. This study just confirms what we’ve been seeing all along.”

 The new analysis examined the total number of Facebook fans and Twitter followers of the eight Republican candidates: Michele Bachmann, Herman Cain, Newt Gingrich, Jon Huntsman, Ron Paul, Rick Perry, Mitt Romney and Rick Santorum from June 2011 to December 13, 2011, and the social media growth rates from July 2011 to December 13, 2011.

 Interestingly, no relationship was found between growth rates on social media and polling numbers, though researchers state it is possible that the sample size was simply too small or that prevailing views of candidates did not change enough over the study period to create a relationship between growth rates and polling data. Researchers go on to state in the report that the sample size was intentionally small to determine if similar size analyses could be helpful for augmenting polling data for campaign managers during election cycles.

 “As the science of social media prediction matures, issues like social media manipulation by spammers and propagandists will need to be addressed, said Einhorn. “But the implications of harnessing social analytics for the purpose of making predictions clearly holds a lot of promise. It also signifies a growing trend within the tech space: he who controls the data, controls the future.”