Human behavior evaluation in Twitter using meta-heuristic algorithm

Social networking sites, like Twitter and Facebook, are quickly becoming one of the most popular tools for social interaction and information exchange. Predicting and evaluating the behavior of users on social networks are considered as the main goal of this research. First of all, SXSW event dataset is considered as a benchmark dataset related to Twitter. After normalization and deletion of the preposition, positive and negative meaning of words are classified into positive and negative labels. Finally, the user behavior in using classified words are investigated by Grey Wolf Optimization (GWO) algorithm. The results reveal the accuracy of GWO method in human behavior evaluation.

Keywords:

Social networks , Evolutionary algorithms , GWO , Twitter , Human behavior