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
