Online social networks are web platforms that provide a variety of services. 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 rapid increase in social media consumption and production have made the analysis of social media and networks a hot topic amongst academic researchers and industry practitioners alike.
SIMBig has become an important venue that has attracted computer scientists, computer engineers, software engineers, and application developers from around the world. 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, the track solicits experimental and theoretical works on social network and media analysis and mining along with their application to real life problems.
Full papers will be reviewed and assessed by 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 best papers could be published in Springer CCIS Series.
We plan to include all the important topics related to social network and media analysis and mining within SNMAM. The topics suitable for SNMAM include, but not limited to:
- 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.
- Mobile computing and applications on social networks.
- Modeling of user behavior and interaction in social networks.
- Information retrieval in social network and media services.
- Business and political impact in social network and media analysis.
- Monitoring social networks and media.
- Analysis of the relationship between social media and traditional media.
- Exploratory and visual data mining of social networks and media data.
- Ethics and privacy in social network and media services.
- Big data issues in social network and media analysis.
- New applications and services arising from big data, social networks and social media.
SNMAM is one of the first tracks grouping related areas such as Big Data, Social Network Analysis, Machine Learning, etc, in Latin America. We would like to thank you in advance for your scientific contribution to the second edition of SNMAM track and look forward to having the opportunity to showcase and disseminate your research.
Authors are invited to submit original and unpublished papers of research and applications for this track. Full papers should be between 5 to 10 pages (including references, tables, and figures). Papers should be written in English and submissions must be in PDF format following the instructions of ACL templates, available here:
Latex Microsoft Word
All the submissions will be refereed by experts in the field based on originality, significance, relevance, quality and clarity. Every submitted paper will be reviewed by at least three program committee members.
Paper registration is required, allowing the inclusion of the paper in the conference proceedings. At least one author of each accepted paper MUST present the paper.
Paper registration and submissions to SNMAM will be handled using the EasyChair system. The address to paper registration here
PhD(c) in Computer Science
Department of Computer Science, ICMC
University of São Paulo,
Email contact: firstname.lastname@example.org
PhD in Computer Science
Department of Computer Science, ICMC
University of São Paulo