Information Extraction from Social Media

Abstract

With the proliferation of social media sites, suchas Twitter, Facebook, and LinkedIn, social streamshave proven to contain the most up-to-date informationon current events. Therefore, it is crucial to extractactivities or events from the social streams, such astweets and it become an ongoing research trend. Mostapproaches that aim at extracting event informationfrom twitter typically use the context of messages.However, exploiting the location information of georeferencedmessages and the profile data are alsoimportant because tweet messages are short,fragmented and noisy, and therefore not includecomplete information about the events. For this, in thispaper, a framework for event-extraction andcategorization from Twitter is proposed. To extract thelocalized related activities, several mining mechanismsand cleaning techniques is used for real-time twittercorpus and various language processing approaches isapplied for categorization the events and then thesystem will display the valuable information for thetargeted domain