Detecting Life Events in Feeds from Twitter

Abstract

Short posts on micro-blogs are characterized by high ambiguity and non-standard language. We focus on detecting life events from such micro-blogs, a type of event which have not been paid much attention so far. We discuss the corpus we assembled and our experiments. Simpler models based on unigrams perform better than models that include history, number of retweets and semantic roles.