Mining Mood Swings on the Real-Time Web

August 24, 2010 | Source: Technology Review

This widget shows current sentiment toward competing Web browsers (Viralheat)

Social-media analytics startupĀ Viralheat is now offering free, real-time access to the data it is collecting on attitudes toward particular topics or products. One of the first customers for this new service — called Social Trends — is ESPN, which plans to use Social Trends to show live popularity rankings for different NFL teams.

Viralheat uses natural-language processing and machine learning to sift through Twitter, Facebook fan pages, viral video sites, and Google Buzz posts to determine the Web’s collective sentiment toward various topics.

Social Trends uses this information to provide a widget that can be embedded on a blog or website showing the sentiment around particular terms. These widgets stay connected to Viralheat’s data stores through an application programming interface (API) and are updated as the company collects more information. Viralheat believes the tool will be particularly useful for news sites wanting up-to-date infographics and for bloggers who want to track trends.