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Special track on Social Network and Media Analysis and Mining (SNMAM 2017)


SNMAM 2017 - Track on Social Network and Media Analysis and Mining
04-06 September 2017 - Lima, PERU

Online Social Networks are web platforms that provide a variety of services. In such platforms users may share locations and community activities, post and tag photos and other media content, as well as contact individuals with similar interests. The rapid growth of social networks, as well as the increase in consumption and production of social media, have made the analysis of social networks one of the most relevant topics amongst academic researchers and industry practioners.
SIMBig has becoming an important venue that has attracted computer scientists, computer engineers, software engineers, and application developers who work on networks and web based-methods. Within the general symposium, the Social Network and Media Analysis and Mining (SNMAM) track will provide a forum that brings both researchers and practitioners to discuss research trends and techniques related to social networks and media. Therefore, it will be welcome experimental and theoretical works on social network and media analysis and mining along with their application to real world problems.
Submissions will be reviwed and assessed by at least to member of the program committee. Accepted papers will be published in the proceedings of SIMBig 2017 as well as indexed on DBLP (see the SNMAM 2016 published papers here:
The authors of best papers will be invited to submit an extended version of their papers for Springer CCIS Series.
31 May 2017    -------> Papers due
30 June 2017   -------> Acceptance notifications
15 July 2017   -------> Camera-ready
30 July 2017   -------> Early bird registration deadline
4-6 September 2017 ---> Conference held in Lima, Peru
SNMAM 2017 has a broad scope. We invite contributions on theory and practice, including but not limited to the following topics.
- Data modeling for social networks and social media
- Dynamics and evolution of social networks
- Topological, geographical and temporal analysis of social networks
- Privacy and security in social networks
- Pattern analysis in social networks
- Crowd sourcing of network data generation and collection
- Community structure analysis in social networks
- Link prediction and recommendation systems
- Propagation and diffusion of information in social networks
- Detection of spam, misinformation and malicious activities in social networks
- Location-based social networks

SNMAM 2017 Chairs:
- Jorge Valverde-Rebaza, University of São Paulo, Brazil ([email protected])
- Alneu de Andrade Lopes, University of São Paulo, Brazil ([email protected])

This post first appeared on Beamtenherrschaft, please read the originial post: here

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Special track on Social Network and Media Analysis and Mining (SNMAM 2017)


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