Communication activity in social networks: growth and correlations

TL;DR

This study analyzes message timing in online communities, revealing long-term correlations and scaling behaviors that influence communication patterns and partner engagement.

Contribution

It uncovers the relationship between growth fluctuations and long-term correlations in social network messaging activity, supported by numerical simulations.

Findings

Long-term persistence in message timing.

Scaling in growth fluctuations related to correlations.

Power-law relationship between number of messages and partners.

Abstract

We investigate the timing of messages sent in two online communities with respect to growth fluctuations and long-term correlations. We find that the timing of sending and receiving messages comprises pronounced long-term persistence. Considering the activity of the community members as growing entities, i.e. the cumulative number of messages sent (or received) by the individuals, we identify non-trivial scaling in the growth fluctuations which we relate to the long-term correlations. We find a connection between the scaling exponents of the growth and the long-term correlations which is supported by numerical simulations based on peaks over threshold. In addition, we find that the activity on directed links between pairs of members exhibits long-term correlations, indicating that communication activity with the most liked partners may be responsible for the long-term persistence in the timing of messages. Finally, we show that the number of messages, $M$, and the number of communication partners, $K$, of the individual members are correlated following a power-law, $K\sim M^\lambda$, with exponent $\lambda\approx 3/4$.