Social TV: Cross-Channel Insights on the ShareThis Platform
Sharing is one of the most trusted and universal of human behaviors. At ShareThis, we have built one of the largest platforms for capturing user shares across more than 2.4 million publishers. Our platform touches more than 95% of the US Internet population and enables a billion social events every month across more than hundred social channels. In this study, we will investigate the social behavior of users on television content. Specifically, we will look into the demographics and psychographics of the audience and explore how they differ across social channels. We will quantify the real time and near real time aspects of the social TV activity and look into the effect of social on engagement around TV content. The key takeaway from the presentation will be insights on social TV as seen on the ShareThis platform and exploring the social behavior across channels.
Saikat is a Data Scientist at ShareThis working on mining the online social behavioral data of hundreds of millions of users. In this role he has been identifying audience segments relevant to brands, understanding the behavior of these segments, and applying these insights to online advertising campaigns. Prior to ShareThis, he was at Intuit where he applied data mining and machine learning techniques to build innovative products such as financial graphs from small business and consumer transactional data, offers and recommendation products using the financial graph, and in-product analytics for increasing conversion and customer retention. He obtained his Ph.D. from SUNY Stony Brook and bachelors from the Indian Institute of Technology and has published extensively in technical and industry conferences.