抄録
A twitter user posts a 140-character-limited text named 'Tweet'. So twitter is called micro-blog. In May of 2010, users have posted 15 billion tweets since the service launched. But, tweets are not like web text, it is more personal, temporary, and short contented. Thus twitter's attributes make it difficult to extract keywords from tweets. In this paper, we introduce topic extraction methods using Probabilistic Latent Semantic Analysis (PLSA), and Latent Dirichlet Allocation (LDA) specified in twitter. We show the novel approach to analyze the contents of Twitter user.
