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Open Calls for Papers

EPJ B Topical Issue: New frontiers in exploring the dynamics of community structure in online social networks

Guest Editors: Shuo Yu, Asif Ali Laghari, Mengmeng Yang, Renaud Lambiotte

Submissions are invited for a Topical Issue of EPJ B on New frontiers in exploring the dynamics of community structure in online social networks.

Social networks have become an important part of our everyday life. These networks have revolutionized the way we live and interact with each other. Numerous applications of social networks go beyond just personal communication, including finding new friends and business contacts as well as organizing public events, or finding people who share similar interests. Understanding the dynamics of community structure in online social networks is important for many reasons. First, such knowledge can help improve marketing strategies since it sheds light on the relationships between users and the products or services sold. Second, this information can be used in the design and development of social networking systems that support these relationships. Third, understanding how communities emerge and evolve will help us better predict future behavior in response to various events. Online social networks have become popular venues for connecting with others and sharing content. However, they also harbor the potential to enable malicious activities by users who intend to harm members of these communities. To help mitigate this threat, it is critical to understand how community structures evolve and what factors affect them. The dynamics of community structure in online social networks have attracted growing interest from many disciplines. Network science, sociology, and social psychology have all contributed to the research community's understanding of how contextual factors influence what individuals perceive as "communities" and how they behave within those communities. However, even though most studies treat individual participation as relatively stable across periods (e.g., by comparing one time period to another or averaging across multiple periods), there is no scientific consensus on how users' behaviors change over time, whether because of changes in their characteristics such as demographics, mood, and personality; or because of trends in technology adoption; or both.

Online social networks (OSNs) are platforms for creating and sharing diverse content. These OSNs allow researchers to collect large-scale data about the structure and dynamics of users' communities of interest. However, many common frameworks treat OSN users as homogeneous entities and ignore their heterogeneous nature; thus, current approaches to studying user communities do not fully examine how community structure is influenced by individual characteristics such as gender or education level. This special issue will address these issues by focusing on how network properties vary across different online communities, including those divided by gender or age groups

Topics to be covered include but are not limited to:

  • The effect of structural factors on community formation and evolution, such as recruitment strategies, size distributions
  • The role of social media in creating and reinforcing gender stereotypes
  • Gender-specific behaviors in online communities (e.g., number of posts, amount of time spent on the site)
  • The relationship between network structure and community dynamics, including factors that drive changes in community size, activity level, and content diversity
  • Dynamics of community formation and dissolution
  • Innovative ways to measure influence or activity within a community based on network properties
  • State-of-the-art methodologies to identify meaningful groups on an OSN by leveraging existing data and communication patterns
  • Methods for detecting and analyzing community structure in online social networks
  • Evolution of community structure over time
  • The impact of community structure on the spread of information and ideas
  • The relationship between community structure and social norms
  • Applications of community detection in online social networks

Original research papers, Reviews, and Colloquium-type articles are welcome. We invite contributors to communicate their intention to submit manuscripts for this Topical Issue to the Guest Editors as soon as possible. Please provide the tentative title of the paper and a short abstract. The full manuscripts should be submitted before the deadline directly to the EPJ B Editorial Office at https://www.editorialmanager.com/epjb/.

Deadline for submission: April 1st, 2024

Submissions should be clearly identified as intended for the Topical Issue on ‘New frontiers in exploring the dynamics of community structure in online social networks’. Papers will be published continuously and will appear as soon as accepted on the journal website. The electronic version of the Topical Issue will contain all accepted papers in the order of publication. All submitted papers will be refereed according to the usual high standards of the journal. More information about EPJ B, including instructions for authors is available here.

Guest Editors:

Dr. Shuo Yu,
School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, 116024, China
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Dr. Asif Ali Laghari,
Computer Science Department, Sindh Madressatul Islam University, Karachi, Pakistan
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Dr. Mengmeng Yang,
Information Security and Privacy Group, Software and Computational Systems Program, Data61-CSIRO, Australia
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Professor Renaud Lambiotte,
Mathematical Institute, University of Oxford, Andrew Wiles Building, Radcliffe Observatory Quar-ter, Woodstock Road, Oxford, OX2 6GG, UK
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Open Access

EPJ B is a hybrid journal offering Open Access publication via the Open Choice programme and a growing number of Springer Compact “Publish and Read” arrangements which enable authors to publish OA at no direct cost (all costs are paid centrally).

Editors-in-Chief
A. Beige, J. Burgdörfer and S. Ptasinska
"I take this opportunity to thank the EPJD editorial office for the rapid and efficient processing of our paper.

Mauro Temporal

ISSN (Print Edition): 1434-6060
ISSN (Electronic Edition): 1434-6079

© EDP Sciences, Società Italiana di Fisica and Springer-Verlag