Akademik Veri Yönetim Sistemi
BCS SGAI Workshop on Social Media Analysis, BCS SGAI SMA 2013 - Workshop Co-located with AI-2013 33rd SGAI International Conference on Artificial Intelligence, BCS SGAI 2013, Cambridge, İngiltere, 10 Aralık 2013, cilt.1110, ss.35-46, (Tam Metin Bildiri)
Newsworthy stories are increasingly being shared through social networking platforms such as Twitter and Reddit, and journal-ists now use them to rapidly discover stories and eye-witness accounts. We present a technique that detects "bursts" of phrases on Twitter that is designed for a real-time topic-detection system. We describe a time-dependent variant of the classictf-idf approach and group together bursty phrases that often appear in the same messages in order to iden-tify emerging topics. We demonstrate our methods by analysing tweets corresponding to events drawn from the worlds of politics and sport. We created a user-centred "ground truth" to evaluate our methods, based on mainstream media accounts of the events. This helps ensure our methods remain practical. We compare several clustering and topic ranking methods to discover the characteristics of news-related collections, and show that different strategies are needed to detect emerging topics within them. We show that our methods successfully detect a range of different topics for each event and can retrieve messages (for example, tweets) that represent each topic for the user.