Social Media Analytics: Data Mining Applied to Insurance Twitter Posts

The use of social media has grown significantly in recent years. With the growth in its use, there has also been a substantial growth in the amount of information generated by users of social media. Insurers are making significant investments in social media, but many are not systematically analyzing the valuable information that is resulting from their investments.

This paper discusses the application of correlation, clustering, and association analyses to social media. This is demonstrated by analyzing insurance Twitter posts. The results of these analyses help identify keywords and concepts in the social media data, and can facilitate the application of this information by insurers. As insurers analyze this information and apply the results of the analysis in relevant areas, they will be able to proactively address potential market and customer issues more effectively.

Keywords: Social media, analytics, data mining, text mining, clustering, association analysis