Studying the attributes of users in Twitter considering their emotional states

Abstract

Positivity and negativity are two important attributes of a person’s emotion and mood. Social media is a very important platform from which we can glean the positivity and negativity attributes of a user based on his/her message postings and interactions with other users. In this paper, we study and analyze a Twitter dataset of more than 130,000 users to understand the nature of their positivity and negativity attributes. We measure behavioral attributes by analysis of social engagement and psychological process. Our analysis is done for two types of networks, positive and negative, to compare the patterns of tweeting, replying and following, and network and time properties. We observe that social media contain useful behavioral cues that have a potential to classify users into positive and negative groups based on network density and degree of social activity either in information sharing or emotional interaction and social awareness. We believe that our findings will be useful in developing tools for predicting positive and negative users and help provide the best recommendation towards helping negative users through online social media.