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SNMAM 2019 : Track on Social Network and Media Analysis and Mining

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Link: https://simbig.org/SIMBig2019/en/snmam.html
 
When Aug 21, 2019 - Aug 23, 2019
Where Lima, Peru
Submission Deadline May 15, 2019
Notification Due Jun 14, 2019
Final Version Due Jul 1, 2019
Categories    social networks   machine learning   big data   network science
 

Call For Papers

OVERVIEW
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The continued growth of online social networks, as well as the increase in consumption and production of social media, have made the analysis of social networks and media one of the most relevant topics of current academic research and industry applications.

SIMBig is one of the first conferences in Latin America grouping related areas, such as Data Science, Machine Learning, Social Network Analysis, and others. Therefore, SIMBig has becoming an important venue that has attracted computer scientist, computer engineers, software engineers, and application developers who work on network 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 Network Science applied on social networks and media data. Moreover, SNMAM welcomes experimental and theoretical works on social network and media analysis and mining along with their application to real world problems.



PUBLICATION
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All papers of SNMAM will be pusblished in the proceedings of SIMBig 2019 with Springer CCIS Series.



IMPORTANT DATES
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May 31, 2019 --) Papers submission
June 21, 2019 --) Notification of acceptance
July 01, 2019 --) Camera-ready versions
August 21 - 23, 2019 --) Conference held in Lima, Peru



TOPICS OF INTEREST
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SNMAM has a broad scope. We invite contributions on theory and practice, including but not limited to the following technical areas:

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
Analysis and mining of Location-based social networks



CONTACT
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SNMAM 2019 Chairs

Jorge Valverde-Rebaza, Visibilia, Brazil (jvalverr@visibilia.net.br)
Alneu de Andrade Lopes, University of São Paulo, Brazil (alneu@icmc.usp.br)

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