SNAMS 2017


Social network analysis is concerned with the study of relationships between social entities. The recent advances in internet technologies and social media sites, such as Facebook, Twitter and LinkedIn, have created outstanding opportunities for individuals to connect, communicate or comment on issues or events of their interests. Social networks are dynamic and evolving in nature; they also involve a huge number of users. Frequently, the information related to a certain concept is distributed among several servers. This brings numerous challenges to researchers, particularity in the data mining and machine learning fields. The purpose of this SNAMS Symposium is to provide a forum for researchers to present and discuss their work which is related to social network analysis. This Symposium is col-located with the 5th International Conference on Future Internet of Things and Cloud (FiCloud-2017), 21-23 August 2017, Prague, Czech Republic .

SNAMS 2017 aims to investigate the opportunities and in all aspects of Social Networks. In addition, it seeks for novel contributions that help mitigating SNAMS challenges. That is, the objective of SNAMS 2017 is to provide a forum for scientists, engineers, and researchers to discuss and exchange new ideas, novel results and experience on all aspects of Social Networks. Researchers are encouraged to submit original research contributions in all major areas, which include, but not limited to:

* Social networks mining
* Social networks security and privacy
* Social networks architecture and growth
* Social networks visualization and large scale data representation
* Geographical aspects of social networks
* Social networks and big data
* Impact of social networks
* Social networks data analysis tools and services on the Cloud
* Opinion mining
* Sentimental analysis
* Community formation, analysis and detection in Social networks
* Community formation, analysis and detection in Social networks
* Personalization of search engines and recommender systems based on social network behavior
* Psychological and criminal studies related to social networks and social networks behavior
* Graphical visualization and analysis of social networks
* Natural language processing applications/studies on social networks

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