Behavior Computing: Modeling, analysis, mining and decision
Human behaviour is made up of complex interdependencies, not least of all because individuals convey actions using the multiple modes of voice, facial and eye movements, hand gesturing and body to interact on a social basis. The modelling and analysis of human behaviour is giving rise to the new discipline of behaviour computing integrating techniques from both computer science and social sciences.
In this new field of behaviour computing, a major distinction over previous behavioural research is a focus on online social networks and the internet impacting behaviour rather than the traditional experimental analysis of the behaviour of animals and organisms. The field of behaviour computing opens up the opportunity for breakthrough advances, discoveries and advanced knowledge to come from outside of social sciences.
Behaviour Computing effectively contextualises statistical and machine learning tools in a series of 23 very interesting chapters embracing models, scenarios and case studies thematically connected with behaviour computing. The end result is a highly presentable book for a wide-ranging audience inclusive of final-year undergraduates or postgraduate students. However, the book requires familiarity with machine learning algorithms and analysis of large datasets and may just prove to be a catalyst for social scientists to leave behind existing pastures and embrace the field of behaviour computing.
Suresh Sood, Advanced Analytics Institute
Behavior Computing: Modeling, analysis, mining and decision, edited by: Longbing Cao, Philip S. Yu
This review was first published by UTS: Newsroom