Optimization research of short text semantic clustering based on the social media

Based on the existing research of Chinese text clustering, this paper proposes an improved algorithm for the optimization of short term semantic clustering based on social media. The method of weighted factor is introduced to optimize text distance formula and related mathematical proof, the calculation process optimization design from text, written text distance calculation algorithm, the simulation experiment is carried out to optimize the clustering results of historical comments online data set using the golden section optimization method. Experimental results show that the proposed method improves the performance of short text clustering in social media. We can grasp the social media in a variety of hot topics on the point of view and position, for the country and social stability and development services.