  Quantitative research of emotions in psychology and machine-learning methods
for extracting emotion components from text messages open an avenue for
physical science to explore the nature of stochastic processes in which
emotions play a role, e.g., in human dynamics online. Here, we investigate the
occurrence of collective behavior of users that is induced by chats with
emotional Bots. The Bots, designed in an experimental environment, are
considered. Furthermore, using the agent-based modeling approach, the activity
of these experimental Bots is simulated within a social network of interacting
emotional agents. Quantitative analysis of time series carrying emotional
messages by agents suggests temporal correlations and persistent fluctuations
with clustering according to emotion similarity. {All data used in this study
are fully anonymized.}
