Emotions online dating community
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.
Consequently, instant communication should require specific tools and models for analysis, that are capable of covering these predominant features.
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.
Our quantitative insights into user's activity patters and their emotional expressions are eventually combined to model interacting emotional agents.
We demonstrate that the stylised facts of the emotional persistence can be reproduced by our model by only calibrating a small set of agent features.
We process our analysis as follows: first, we look into the communication patterns of instant online discussions, to find out about the average response time of users and its possible dependence on the topics discussed.
This shall allow us to identify differences between instantaneous chatting communities and other forms of slower, persistent communication.
Remarkably, we find that most users are very persistent in expressing their positive or negative emotions - which is not expected given the variety of topics and the user anonymity.This success indicates that our modeling framework can be used to test further hypothesis about emotional interaction in online communities.A) Schema of the evolution of a conversation in an IRC channel.At every time step, a user enters a post expressing a positive, negative, or neutral emotion.B) Probability distribution of the user activity over all the IRC channels.