  We study the changes in emotional states induced by reading and participating
in online discussions, empirically testing a computational model of online
emotional interaction. Using principles of dynamical systems, we quantify
changes in valence and arousal through subjective reports, as recorded in three
independent studies including 207 participants (110 female). In the context of
online discussions, the dynamics of valence and arousal are composed of two
forces: an internal relaxation towards baseline values independent of the
emotional charge of the discussion, and a driving force of emotional states
that depends on the content of the discussion. The dynamics of valence show the
existence of positive and negative tendencies, while arousal increases when
reading emotional content regardless of its polarity. The tendency of
participants to take part in the discussion increases with positive arousal.
When participating in an online discussion, the content of participants'
expression depends on their valence, and their arousal significantly decreases
afterwards as a regulation mechanism. We illustrate how these results allow the
design of agent-based models to reproduce and analyze emotions in online
communities. Our work empirically validates the microdynamics of a model of
online collective emotions, bridging online data analysis with research in the
laboratory.

Human-Computer Interaction