Mining and analyzing social networks is now becoming a very popular research area not only for data mining and web mining but also social network analysis. Data mining is a technique that has the ability to process and analyze large amounts of data and by this to discover valuable information from the data. In recent years, due to the booming of social communications and social network-based web services, data mining has become a very important and powerful technique to process and analyze such large amount of data.
Recently, many researchers are focusing on developing new data mining techniques and algorithms, or devoting to improve traditional mining techniques for social network analysis. However, it is meaningless, if the discovered valuable and useful data have not been applied in real application environment. Social data are the aggregations of communication interaction and experience of people, and it if useful to leverage this type of data for decision making. Thus, it could be an important time to shift the research focus to an application area, such as decision support.
The workshop was firstly organized in conjunction with ASONAM 2009 conference in Athens, Greece. MSNDS 2010 was in conjunction with ASONAM 2010 in Odense, Denmark. MSNDS 2011 was in conjunction with ASONAM 2011 in Kaohsiung, Taiwan. MSNDS 2012 was held with ASONAM 2012 in Istanbul and MSNDS 2013 was conjunction with ASONAM 2013 in Niagara Falls, Canada and MSNDS 2015 was conjunction with ASONAM 2015 in Paris, France and MSNDS 2016 was conjunction with ASONAM 2016. Thus, it is also valuable to include this workshop again in ASONAM 2017 to bring together researchers who are interested in this topic.
This workshop invites papers of the following topics, but never exclusive:
- Mining and analyzing social data for decision support
- Mining social web services for decision support
- Algorithms for mining social networks for decision support
- Matching engines and interfaces for decision support systems
- System architectures
- Intelligent and multi-agent based decision support systems
- Social decision support systems
- Semantic Analysis for Decision Support
- Opinion Mining and Sentiment Analysis
- Big Data Issue in Mining and analyzing social data for decision support
- Experiment and implementation
- Leveraging social data for decision support in healthcare
- Case studies and empirical studies
Full paper manuscripts must be in English with a maximum length of 6 pages or short paper 4 pages (using the IEEE two-column template).
Submissions should be in PDF and include the title, author(s), affiliation(s), e-mail address(es) and abstract on the first page. The submission link is: https://easychair.org/conferences/?conf=msnds2017
At least one author of each accepted paper must register for the conference and is expected to attend the workshop and present the work as scheduled in the workshop program.