ABSTRACT
The Social media (SM) websites contain social data posted by users which are used to comprehensively understand the human behaviors and society characteristics. This chapter gives an overview of online SM websites characteristics, content analysis method for SM, and network methods for SM. Data mining is a relatively new field that has successfully created many methods and algorithms for analyzing big data for real-world application. Data mining processes involve either statistical or machine learning algorithms in the analysis stage to get the pattern from the big data of SM. The most used machine learning algorithms to analyze the unstructured data from SM websites are supervised machine learning methods. In supervised learning algorithms, variables can be split into independent variables and dependent variables. Breadth-first search is a graph traversal algorithm that is used to crawl SM websites. It shows high-order optimality and ease of implementation, particularly in undirected graphs.
