Personal Life Event Detection from Social Media

Creating video clips out of personal content from social media is on the rise. MuseumOfMe, Facebook Lookback, and Google Awesome are some popular examples. One core challenge to the creation of such life summaries is the identification of personal events, and their time frame. Such videos can greatly benefit from automatically distinguishing between social media content that is about someone’s own wedding from that week, to an old wedding, or to that of a friend. In this paper, we describe our approach for identifying a number of common personal life events from social media content (in this paper we have used Twitter for our test), using multiple feature-based classifiers. Results show that combination of linguistic and social interaction features increases overall classification accuracy of most of the events while some events are relatively more difficult than others (e.g. new born with mean precision of .6 from all three models).