  Using agent-directed simulations, we investigate fluctuations in the
collective emotional states on a chat network where agents interchange messages
with a fixed number of moderators and emotional Bot. To design a realistic chat
system, the interaction rules and some statistical parameters, as well as the
agent's attributes, are inferred from the empirical chat channel
\texttt{Ubuntu}. In the simulations, the Bot's emotion is fixed; the moderators
tune the level of its activity by passing a fraction $\epsilon$ of messages to
the Bot. At $\epsilon \gtrsim 0$, the collective emotional state matching the
Bot's emotion polarity gradually arises; the average growth rate of the
dominant emotional charge serves as an order parameter. Due to self-organizing
effects, the collective dynamics is more explosive when positive emotions arise
by positive Bot than the onset of negative emotions in the presence of negative
Bot at the same $\epsilon$. Furthermore, when the emotions matching the Bot's
emotion polarity are spread over the system, the underlying fractal processes
exhibit higher persistence and stronger clustering of events than the processes
spreading of emotion polarity opposite to the Bot's emotion. On the other hand,
the relaxation dynamics is controlled by the external noise; the related
nonextensive parameter, estimated from the statistics of returns, is virtually
independent of the Bot's activity level and emotion contents.
