SIMBig Conference 2022

Call for Papers

The Social Network and Media Analysis and Mining (SNMAM) is a forum that brings both researchers and practitioners to discuss research trends and techniques related to the analysis and mining of social network and media data. The 7th SNMAM event will be organized as a track of SIMBig 2022 in Lima, Peru, as an interdisciplinary venue for computer scientists, computer engineers, software engineers and application developers who work on networks and web-based methods.

Social network is a structure formed by a set of entities with some patterns of social interaction. Social Network Analysis (SNA) is focused on uncovering these patterns through the use of network science and graph theory. In the last decades, online social networks (OSNs) have become the most widely used web platforms due to the variety of services they offer to their users. This explosion has led to the diversification of both content (text, images, audio and other) and the sources (e.g. newscasts, newspapers and other companies) in OSNs. The need for processing and analyzing this content as well as understanding its impact on users' lives, has allowed for the rapid development of various techniques for mining and analysis of social media data.

Therefore, SNMAM welcomes experimental and theoretical works on analysis and mining of social network and social media data along with their application to real-world problems. Young scientists and researchers from scientific centers, students and graduates, as well as industrial partners are welcome to participate.

Scope and Topics

Authors are invited to submit original and innovative papers that break new ground, present insightful results based on your experience in Data Science. SIMBig 2022 has a broad scope, and specific topics of interest include (but are not limited to):

Crowdsourcing of social network and media data generation and collection
Data preparation and data modeling for social networks and social medias
Exploratory and visual data analysis of social network and media data
Identification and discovery of dynamics and evolution patterns of social network and media data based on data mining and machine learning approachess
Topological and spatio-temporal aspects in social networks and social media
Large-scale graph, search and time series algorithms on social networks
Social network analysis and mining tasks:

Anomaly and outlier detection
Community discovery
Link and node classification
Link and node prediction
Entity resolution
(Social) Graph construction

Data mining applications on social network and media data:

Recommender systems
Opinion and suggestion mining
Sentiment analysis
Hate speech, misbehavior and toxic language detection
Activity prediction
Echo chambers, homophily, filter bubbles, and polarisation analysis
Event detection
Fake news detection
(Epidemic) Spreading and rumors detection

Applications of social network and media in business, engineering, scientific, medical and public health domains (e.g., social behavior analysis due to COVID-19), terrorism and/or criminology, fraud detection, politics, cyberbullying, and case studies
Analysis and mining of location-based social networks, urban (social) networks, multilayer social networks and others
Social media monitoring and analysis
Ethics, privacy and security in online social networks and social media platforms
Tools and infrastructures for social networking platforms and web communities
New applications and services arising from big data, social network analysis and social media.

Long Papers

Long Papers are limited to a total of 13-16 pages, including all content and references, and must be in PDF formatted with the Springer publication format.

Short Papers

Short Papers are limited to a total of 7-12 pages, including all content and references, and must be in PDF formatted with the Springer publication format.

Paper Submission Guidelines

All research submissions must be in English.
Submissions must be in PDF, formatted with the Springer Publications format. For details on the Springer style, see here.

LATEX

MICROSOFT WORD

Please, note that SNMAM submission is double-blind. Therefore, authors need to ensure that their manuscripts are prepared in a way that does not reveal their identity. Failure to follow this instruction will result in an automatic rejection of submission.
Papers accepted for publication: the camera-ready version of your paper must be submitted only using Latex format. This is to ensure proper insertion of the manuscript in proceedings. Failure to follow this instruction will result in disregard of submission.

Easychair Submissions Website

Submissions for SNMAM 2022 here.

Program Committee

Alexandre Donizeti Alves, Federal University of ABC, Brazil
Alexandre Levada, Federal University of São Carlos, Brazil
Ankur Singh Bist, Govind Ballabh Pant University of Agriculture and Technology, India
Aurea Rossy Soriano Vargas, University of Campinas, Brazil
Brett Drury, Liverpool Hope University, England
Conceição Rocha, INESC/CPES, Portugal
Daniela Godoy, UNICEN University, ISISTAN Research Institute, Argentina
Diego Furtado Silva, University of São Paulo, Brazil
Geraldo Pereira Rocha Filho, University of Brasília, Brazil
Katarzyna Musial-Gabrys, University of Technology Sydney, Australia
Marco Aurélio Domingues, State University of Maringá, Brazil
Mathieu Roche, Cirad-TETIS, France
Murilo Naldi, Federal University of São Carlos, Brazil
Muhammad Nihal Hussain, University of Arkansas at Little Rock, USA
Newton Spolaôr, Western Paraná State University, Brazil
Pascal Poncelet, University of Montpellier, France
Pedro Henrique Luz de Araujo, University of Vienna, Austria
Pedro Nelson Shiguihara Juárez, Universidad San Ignacio de Loyola, Peru
Rafael Giusti, Federal University of Amazonas, Brazil
Rafael Rodrigues, University of São Paulo, Brazil
Rafael Santos, National Institute for Space Research, Brazil
Renan Padua, iFood, Brazil
Ricardo Campos, Ci2 - Polytechnic Institute of Tomar; INESC TEC, Portugal
Ricardo Marcacini, University of São Paulo, Brazil
Ronaldo Prati, Federal University of ABC, Brazil
Sabrine Mallek, ICN Business School, France
Solange Rezende, University of São Paulo, Brazil
Sylvia Iasulaitis, Federal University of São Carlos, Brazil
Vinicius Borges, University of Brasília, Brazil
Willy Ugarte, University of Applied Sciences, Peru

Organizers

Jorge Valverde-Rebaza

PhD in Computer Science

Department of Scientific Research, Visibilia

São Paulo, Brazil

Alan Demétrius Baria Valejo

Ph.D. in Computer Science

Federal University of São Carlos (UFSCar)

São Carlos, Brazil

Fabiana Rodrigues de Góes

PhD(c) in Computer Science

University of São Paulo (USP)