As the rapid growth of user-generated data from social networks, wikis and social tagging systems, it is necessary to understand the high-level semantics and user subjective perceptions from such a large volume of data. Emotions or sentiments are one of the most important aspects as the user-generated data are always with emotional loads of their creators. Along with the development of the computational techniques for sentiment analysis and opinion mining, the increasing psychological and cognitive models/theories are exploited for modeling sentiments and emotions by incorporating with social computing techniques such as social network and personalization, mining user reviews, user profiling in social network and so on. Connecting affective/sentimental models and social computing techniques not only can facilitate the understanding big data in at semantic-levels but also improve the performance of various social computing applications in the big data era. It combines affective/sentimental models with social computing as a promising direction and offers opportunities for developing novel algorithms, methods and tools.
The International Workshop on Affective and Sentimental Computing (ASC 2017) in conjunction with the 4th IEEE International Conference on Big data and smart Computing (BigComp 2017) will bring together the academia, researchers, and industrial practitioners from computer science, information systems, psychology, behavior science, and organization science discipline, and provide a forum for recent advances in the field of sentiment analysis, affective computing, emotion detections, and opinion mining from the perspectives of various computing techniques.