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.

This special issue aims to capture the recent progresses by 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.

Topics of interest include, but are not limited to the exploitation of the affective/sentimental models from psychology and cognitive sciences for big data, the identification of emotions/sentiments underlying big data for efficient algorithms for big data management, and the application of affective/sentimental models with social computing techniques in research fields related to (but not limited):

- Sentiment identification & classification
- Emotion identification & classification
- Opinion and sentiment summarization
- Sentiment analysis for social media
- Affective computing for social media
- Time evolving sentiment & emotion analysis
- Knowledge management for affective computing
- Concept-level sentiment analysis
- Social media and social network analysis
- Affective/Sentimental computing for e-learning
- Affective/Sentimental computing for financial data mining
- Affective/Sentimental computing for e-commerce
- Natural language processing techniques for affective computing
- Social ranking
- Social network analysis
- Social tagging analysis
- Affective/Sentimental computing for user modeling
- Data mining algorithms for affective computing
- Big social data analysis
- Information fusion for affective computing

Paper Submission
Authors should follow the instructions given at the International Journal of Machine Learning
and Cybernetics website:
http://www.springer.com/engineering/computational+intelligence+and+complexity/journal/13042

Important Date
April 1, 2017: Due date for full papers submission (extended)
June 1, 2017: Notification of paper to authors (extended)
July 1, 2017: 1st paper revision due (extended)
August 1, 2017: Notification of acceptance (extended)

Guest Editors
Haoran Xie, The Education University of Hong Kong, Hong Kong
Tak-Lam Wong, The Education University of Hong Kong, Hong Kong
Fu Lee Wang, Caritas Institute of Higher Education, Hong Kong
Raymond Wong, University of New South Wales, Australia
Xiaohui Tao, University of Southern Queensland, Australia
Ran Wang, Shenzhen University, China