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Different from other types of online communication, such as blogs or fora where entries are posted at a given time (decided by the writer), IRC chats are instantaneous in real time, i.e.users read while the post is written and can react immediately.Our dataset (described in detail in the data section), consists of 20 IRC channels covering topics as diverse as music, sports, casuals chats, business, politics, or computer related issues – which is important to ensure that there is no topical bias involved in our analysis.For each channel, we have consecutive daily recordings of the open discussion over a period of 42 days, which amounts to more than 2.5 million posts in total generated by more than 20.000 different users.This type of interaction requires much higher user activity in comparison to persistent communication e.g. Further, it is more spontaneous, often leading to emotionally-rich communication between involved peers.
And then, are we able to match these findings with a dynamic model that is able to generate insights into their origin?
In this paper, we provide both: a new way of analysing data from online chats, and a model of interacting agents to reproduce the stylized facts of our analysis.
In addition to the activity patterns of users, we also analyse and model their emotional expressions that trigger the interactions of users in online chats.
While our assumptions about agent's emotional expressions are rooted in psychology, the model allows to test different hypothesis regarding their emotional impact in online communication.
How do human communication patterns change on the Internet?