Facilitating analysis of audience reaction on social networks using content analysis: A case study based on political corruption

Abstract

Today, once a political corruption case takes place, it is rapidly viralized along the Internet where people can react by posting their opinions through social networks. Such audience reaction is clearly interesting but complex to analyze as people employs stereotypes, metaphors, and ironies expressed in an informal language hard to interpret. In this paper, we present how content analysis can help us to uncover the hidden meaning of a message. We focus here on the automated analysis of two political corruption cases and its corresponding opinions through social networks. In particular, one case involves the current government while the second one mostly involves the opposite side. Interesting results are gathered where the use of Content Analysis allows us to easily process the social network information in order to provide clear feedback.