Abstract:

With the popularity of microblog, hot topic detection on microblog has been a hot area of research. Regarding the instantaneity of microblog as a point of penetration, the paper proposes a method of hot topic detection based on change of term energy by studying the change of term energy at different time domain. Based on traditional topic aging theory, the method divides all microblog data into different microblog windows, and introduces the concept of acceleration in physics, which uses the acceleration of terms to describe the change of the speed of the terms in the adjacent window. The paper combines the term acceleration and term weight into a compound weight to quantize term energy better. The paper uses double-conditional probability context similarity computing method based on single-conditional probability, and adds document distribution similarity to decrease the probability of topic confusion. The experiments show that the method is effective and stable in robustness. Compared with single-conditional probability context similarity model, the modified context similarity model has better clustering effect in different keyword detection methods.

Key words: hot topic detection, term energy, acceleration, context similarity