Data and Content Analysis for Social Network Using LDA Text Model

Abstract

WhatsApp is a popular cross-platform application for communicating and connecting people. In this paper, the author analyzes massive data from WhatsApp public groups and obtains so-called tacit knowledge and social complex knowledge. During the processing, the author uses LDA(Latent Dirichlet Allocation) model to analyze the content which helps us to be aware of many aspects from public groups such as social trend, sentiment analysis and other hidden information. In the end, author get the results about topic for each group and the occurrence of words for each topic.