Introduction

For more than a century, social networks have been studied in a variety of disciplines including sociology, anthropology, psychology, and economics. The Internet, the social Web, and other large-scale, socio-technological infrastructures have triggered a growing interest and significant methodological advancements in social network analysis and mining. Method development in graph theory, statistics, data mining and machine learning, and statistical mechanics is inspired by new research problems and, in turn, opens up further possibilities for application. These spiraling trends have led to a rising prominence of social network analysis and mining methods and tools in academia, politics, security, and business.
The international conference series on Advances in Social Network Analysis and Mining (ASONAM 2022) provides an interdisciplinary venue that brings together researchers and practitioners from a broad variety of fields to promote collaborations and exchange of ideas and practices. ASONAM 2022 is intended to address important aspects with a specific focus on emerging trends and industry needs. The conference solicits empirical, experimental, methodological, and theoretical research reporting original and unpublished results on social network analysis and mining along with applications.

Committee

Steering Chair

Reda Alhajj,   University of Calgary, Calgary, Canada

Honorary-Chair

Christian Jacob,   University of Calgary, Canada Frans N. Stokman,   University of Groningen, Netherlands

General-Chairs

Nitin Agarwal,   University of Arkansas at Little Rock, USA
Zongmin Ma,   Nanjing University of Aeronautics and Astronautics, China
Jon Rokne,   University of Calgary, Canada

Program Committee Chairs

Jisun AN,   Singapore Management University, Singapore
Chelmis Charalampos,   University at Albany SUNY, USA
Walid Magdy,   University of Edinburgh, UK

Industry-Track Chairs

Masaomi KIMURA,   Shibaura Institute of Technology, Japan
Faraz Zaidi,   Peel Region, Canada
Jiabin Zhao,   Cisco Inc, USA

Workshops Chairs

Mayank Kejriwal,   ISI, USA
I-Hsien Ting,   National University of Kaohsiung, Taiwan
Giacomo Vaccario,   ETHZ, Switzerland

Tutorial Chairs

Carmela Comito,   CNR-ICAR and University of Calabria, Italy
Hakim Hacid,   Zayed University, UAE
Radu Marculescu,   University of Texas, USA

Multidisciplinary Track Chairs

Candice Lanius,   University of Alabama in Huntsville, USA
Sandra Mitrovic,   Istituto Dalle Molle di Studi sull'Intelligenza Artificiale, Switzerland
Chris J. Kuhlman,   University of Virginia, USA

PhD Forum and Posters Track Chairs

Elio Masciari,   University of Naples Federico II, Italy
Deqing Yang,   Fudan University, China

Demos and Exhibitions Chairs

Keivan Kianmehr,   Amazon Inc., Canada
Tansel Ozyer,   Ankara Medipol University, Turkey

Sponsorship Chairs

Thirimachos.Bourlai,   West Virginia University, USA
Jalal Kawash,   University of Calgary, Canada
Mehmet Kaya,   Firat University, Turkey
Peter Peng,   University of Calgary, Canada

Publicity Chairs

Buket Kaya,   Firat University, Turkey
Kashfia Sailunaz,   University of Calgary, Canada

Publication Chairs

Min-Yuh Day,   National Taipei University, Taiwan
Panagiotis Karampelas,   Hellenic Air Force Academy, Greece

Registration Chairs

Jalal Kawash,   Canada
Mehmet Kaya,   Turkey

Web Chair

Tansel Ozyer,   Ankara Medipol University, Turkey

Call for paper

Important date

2022-06-09
Draft paper submission deadline
2022-09-10
Draft paper acceptance notification
1970-10-10
Final paper submission deadline

For more than a century, social networks have been studied in a variety of disciplines including sociology, anthropology, psychology, and economics. The Internet, the social Web, the Internet of Things, sensor networks, other socio-technological infrastructural advancements at large-scale, have triggered a growing interest and significant methodological advancements in social network analysis and mining. Furthermore, method development in graph theory, graph algorithms, statistics, data mining and machine learning, and statistical mechanics is inspired by new research problems. This, in turn, opens up further possibilities for a rich set of applications. These spiraling trends have led to a rising prominence of social network analysis and mining methods and tools in academia, politics, security, and business.

The international conference series on Advances in Social Network Analysis and Mining (ASONAM) provides an interdisciplinary venue that brings together researchers and practitioners from a broad variety of fields to promote collaborations and exchange of ideas and practices. ASONAM is intended to address important aspects with a specific focus on emerging trends and industry needs. The conference solicits empirical, experimental, methodological, and theoretical research reporting original and unpublished results on social network analysis and mining along with applications. 

Submission Topics

 More specialized topics within ASONAM 2022 include, but are not limited to:

Techniques

- Data collection and quality

- Big data and scalability

- Deep learning and embeddings

- Statistical learning

- Algorithms and techniques

- Visualization

- Modeling and simulation

- Explainable network analysis

Problems

- Centrality and roles

- Community detection

- Link prediction

- Information diffusion

- Influence propagation

- Anomaly detection

- Network macro structures

- Network evolution

- Emergence

- Privacy and security

- Collective behavior

- Crowd sourcing

- Social Recommender Systems

- Misinformation and Misbehavior Analysis and Detection

- Reputation and Trust in Social Networks

- Fairness Bias and Transparency in Social Media

Application domains

- Attributed networks

- Online and offline social networks

- Multirelational, multidimensional, multi-aspect, multilayer networks

- Feature-rich networks

- Time-evolving networks

- Probabilistic networks

- Semantic networks

- Social geography and spatial networks

- Social, cultural, and cyber anthropology

- Policy impact and analysis

- Networks in biology and ecology

- Digital Humanities

 

Guidlines

To fully embrace the fast-growing and vigorously dynamic trend of social network approaches and applications, ASONAM 2022 is eager to consider any breakthroughs in social network analysis and mining in the broadest possible sense.

General areas of interest to ASONAM 2022 include information science and mathematics, communication studies, business and organizational studies, sociology, psychology, anthropology, applied linguistics, biology and medicine.

The papers will be reviewed and assessed by the program committee. Full paper manuscripts must be in English with a length of 8 pages using the IEEE two-column template. We solicit also short paper with a maximum length of 4 pages. Submissions should include the title, author(s), affiliation(s), e-mail address(es), and abstract on the first page.

Papers will be accepted for the conference based on the reviewers' comments on their originality, timeliness, significance, relevance, and clarity of presentation. A Best Paper Award ceremony will be organized at the banquet. If the paper is accepted, the paper will appear in the proceedings of the conference if one author presents the paper at the conference and at least one author registers as a full conference participant.

Publications

Accepted and presented papers will be included in the Conference Proceedings and forwarded for inclusion in IEEE Computer Society Digital Library (CSDL), IEEE eXplore, and the ACM Digital Library. The conference proceedings will be submitted for El indexing through INSPEC by the IEEE. Proceedings will be included in several indexes, e.g., Web of Science, SCOPUS, etc.

If you have any questions on ASONAM 2022, please send email to asonam2022 (AT) gmail (dot) com.

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Important Date

  • Conference Date

    Nov 10

    2022

    to

    Nov 13

    2022

  • Jun 09 2022

    Draft paper submission deadline

  • Sep 10 2022

    Draft Paper Acceptance Notification

  • Nov 13 2022

    Registration deadline

Sponsored By
ACM SIGKDD - Special Interest Group on Knowledge Discovery and Data Mining
IEEE Computer Society
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