Brownian Agents and Active Particles: Collective Dynamics in the Natural and Social Sciences
Brownian Agents and Active Particles: Collective Dynamics in the Natural and Social Sciences
Determining the sentiment of opinions
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Emoticons and Online Message Interpretation
Social Science Computer Review
A DIMENSIONAL MODEL FOR CULTURAL BEHAVIOR IN VIRTUAL AGENTS
Applied Artificial Intelligence - Intelligent Virtual Agents
Docking agent-based simulation of collective emotion to equation-based models and interactive agents
SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
Sentiment in short strength detection informal text
Journal of the American Society for Information Science and Technology
Emotion-Oriented Systems: The Humaine Handbook
Emotion-Oriented Systems: The Humaine Handbook
The good, the bad and the neutral: affective profile in dialog system-user communication
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part I
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part I
Affect listeners: acquisition of affective states by means of conversational systems
COST'09 Proceedings of the Second international conference on Development of Multimodal Interfaces: active Listening and Synchrony
Sentiment strength detection for the social web
Journal of the American Society for Information Science and Technology
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Online communications involve an emotional component that influences the behaviour of internet users. Datasets on online communication allow for modelling emotional effects on individual and collective behaviour of users to make predictions about behaviour in online chat environments. One application of such models is decision-support for online bots that interact with users in real-time for studying the role of emotions in online communication, Affect Listeners, requiring short-term predictions about current participants. We describe an agent-based simulation of individuals' emotional interaction online based on automatic annotation of the affective content of exchanged messages. In particular, we focus on using this model to derive a default model, a 'personality', for new users joining an environment based on already observed users.