What’s Up In Kalamazoo? Topsy Updates Geo-Inference Model To Boost Brands’ Location-Specific Insight
Real-time social analytics company Topsy has updated its geo-inference model so that brands can better track location-specific trends popping up among Twitter users. Its tool now can identify the origin of over 95 percent of tweets at the country level, 50 percent of tweets at the state level, 30 percent of tweets at the county level, and over 25 percent of tweets at the city level.
Less than two percent of tweets include latitude and longitude data, which is available when users opt in to share that location information with Twitter from their mobile devices, Topsy says. (That, by the way, appears to be an uptick from late last year, when Topsy noted that just 1 percent of tweets had geo-tagging enabled; see this article.) Topsy’s model leverages that data when available and adds location names from users’ profiles, tweet text, language, use of local websites and other signals to help infer location. Topsy analyzes over 450 million tweets every 24 hours, and geo-encodes each tweet in real time.
Machine learning is employed to automatically discover which signals are accurate predictors of location. “The key to enabling this machine learning is having a full history of Tweets easily accessible,” says Jamie de Guerre, SVP product and marketing. “Topsy’s multi-year index of tweets enables us to draw correlations between signals in conversations and tweets that have location information to develop this powerful inference.”
Among organizations that have used Topsy’s previously existing location capabilities is the Boston Globe. Earlier this month it employed the capability to help inform this story about how Boston changes during the summer when all the students leave. “Turns out Twitter activity drops nearly 20 percent during the summer,” de Guerre says. Writes the Globe: A separate analysis by the firm Topsy showed that the number of Twitter messages sent from the Boston area last year — including the city itself as well as Cambridge, Somerville, Medford, and Newton — clocked in at 7,241,994 in October and just 6,101,800 in July.
For brand users, the geo-location enhancement that provides insight in its Topsy Pro platform is more about creating detailed local market profiles to show differences in local customer’s interests, sentiment and views of the brand; using local sentiment data to determine where an existing offering or service is popular and in what regions it needs a boost prior to a product launch; build local campaigns by also leveraging its alerting capabilities for notifications about when sentiment changes or trends begin having relevance in a particular area; or optimizing promoted tweets for a local market.