Community and important actors analysis with different keywords in social network

Abstract

Twitter has hundreds of millions of users around the world. Using the Twitter as a social network analysis material is very much in demand. Social network analysis can analyze groups and actors of a social network so that it can detect early behaviors that will be performed by groups and actors. But social network analysis in general has not shown strong groups and actors because it uses only one keyword. As a result, this method is quite difficult in detecting early events of a group and actors, especially those associated with cyberterrorist. For that, it needs a method of social network analysis so that the group and the actors produced are really strong and can be detected early behavior that will be done group and actors. The method in question is the use of several different keywords but have the same topic. With this method, it can be obtained a network pattern of groups and powerful actors related to the desired topic so that it can detect earlier behavior that will be done groups and actors. The results obtained are different keywords but have a high value of similarity topics can produce groups and actors are getting stronger. It can increase in the value of graph metric. So this method is feasible to search relationships between different keywords to find the powerfull community and important actor in social network.