We analyze emotionally annotated massive data from IRC (Internet Relay Chat) and model the dialogues between its participants by assuming that the driving force for the  discussion is the entropy growth of emotional probability distribution. This process is  claimed to be responsible for a power-law distribution of the discussion lengths  observed in the dialogues. We perform numerical simulations based on the noticed  phenomenon obtaining a good agreement with the real data. Finally, we propose a method  to artificially prolong the duration of the discussion that relies on inserting into  dialogues appropriate comments  when the entropy of emotional probability distribution reaches the critical threshold.

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