Discrete chat room
Round the clock activities of Internet users put us into the comfortable situation of having massive data from various sources available at a fine time resolution. Which aggregated measures are most appropriate to capture how new technologies affect our communicative behavior?
And then, are we able to match these findings with a dynamic model that is able to generate insights into their origin?
Prior to the very common social networking sites of today, IRC channels provided a safe and independent way for users to share and discuss information outside traditional media.
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 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.
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.