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Emotional communication patterns in online chat communities

Antonios Garas, David Garcia Becerra, Frank Schweitzer, Marcin Skowron

Real-time communication tools, like chats or instant message services, have an increasing popularity for both casual and professional interactions. These platforms allow us to study the patterns of human behavior in emotional communication through the messages written by people participating in these conversations. We study a dataset composed of logs from Internet Relay Chat (IRC) channels, in which a large amount of users share comments in real time. We use a sentiment analysis tool to extract the emotions expressed in each comment, classified as positive, negative, or neutral. Statistical analysis of the time delays between user messages show that people in chatrooms follow similar principles as in other means of communication. Furthermore, the time dynamics of the whole conversation shows the presence of long-range correlations. We analyze the persistence of the emotional expression of individuals, i.e. how likely they are to express a similar sentiment as in the previous message. We find that most of the users behave in an emotionally persistent way, while some of them have a more random or anti-persistent behavior. Even under the presence of this heterogeneity, there is persistence in the channel as a whole. These results indicate the presence of social norms of emotional expression, as well as the existence of social links between users under the fast communication of a chatroom. We have developed and analyzed a model for the exchange of emotions online that shows the same features as the IRC data, where collective emotions emerge from individual behavior and communication.

Keywords: online communication, social norms, agent-based modeling, Publications List Interact

Citation: In Proceedings of the International Society for Research on Emotion Conference, ISRE 2011