Social Network Analysis and Mining - Special Issue on Collective intelligence on Web and Social Media
Call for Papers
“Collective intelligence on Web and Social Media”.
The fast expansion and pervasive use of online resources like the Web, Microblogging sites and Social Media is making available an enormous and continuous stream of user-generated contents containing invaluable information that can be used to understand, in near real time, human life dynamics worldwide. Besides, social geo-tagged data combines textual, temporal, geographical and network data, opening up unique opportunities to study the interplay between human mobility and social structure.
The tremendous growth in the use of Social Media has led to radical paradigm shifts in the ways we communicate, collaborate, consume, and create information. Our focus in this special issue is on the reciprocal interplay of Social Media and Collective Intelligence. Collective Intelligence (CI) is traditionally understood as the intelligence emerging from the interaction between interconnected, communicating individuals. Although individually each person has diverse knowledge or differing beliefs, their collective intelligence provides accurate data. Collective intelligence can be harnessed from social media through a variety of means and can be beneficial to all sectors of human life. Surveys and polls are available on sites like Facebook and LinkedIn, Twitter, allowing to identify trends and patterns in people’s opinions.
By monitoring the Likes, shares, and comments on social networking sites, it is possible to catch patterns arise in people’s viewpoints that show the popularity of one opinion over another, increasing exposure to the product. In this context, Artificial intelligence (AI) plays a key role. AI is transforming our world, changing the landscape of key sectors like healthcare, mobility, finance, urban contexts. With the increasing availability of geo-tagged social data and rapid progress of machine learning and deep learning algorithms, AI and big data analytics are enabling unprecedented analysis of such novel data sources. Pervasive knowledge and collective intelligence is a cutting-edge research area across diverse fields and disciplines with the common objective of addressing challenging issues and questions about human phenomena and behavior through the lens of web and social media while introducing novel tools to model and process huge amount of unstructured big data. The Special issue will be a new venue for bringing researchers from different disciplines in the fields of Pervasive Computing, Web and Social Media to discuss and promote ideas and practices about pervasive knowledge and collective Intelligence in this fields. In this regard, we solicit theoretical as well as application[1]oriented research studies on relevant topics related to new perspectives in social theories, complex networks, data science, knowledge management, comprising methodologies, algorithms, evaluation benchmarks and tools for the development and application of algorithms for analyzing web and social media. The special issue solicits empirical, experimental, methodological, and theoretical research reporting original and unpublished results on social media analysis and mining along with applications to real life situations.
This can mean new models, new datasets, new algorithms, or new applications. Topics of interest include, but are not limited to:
• Information and Web mining;
• Trend and Hot Topic Identification;
• Social Media for Smart Cities;
• Social Network Analysis;
• Semantic Network Analysis;
• Trust, Reputation, social control and privacy;
• Collective Intelligence;
• Crowdsorcing;
• Information Reliability;
• Web and Content authenticity;
• Dynamic Social Media Monitoring;
• Sentiment and Natural Language Processing;
• Early warnings of disease outbreaks such as seasonal influenza and pandemics;
• Centrality/influence of social media publications and authors;
• Classifying and clustering of geo-temporal data in high dimensional spaces;
• Novel architectures for scalable data analysis and mining;
• Mobility Mining;
• Community discovery and analysis;
• Large-scale graph algorithms for social network analyss;
Key Dates
Deadline for Submission: 28 February, 2023
First Reviews Due: 1 May, 2023
Revised Manuscript Due: 1 June, 2023
Final Decision: 15 July, 2023 Short description on how the special issue will be advertised so as to ensure a sufficiently wide range of authors and high quality papers In order to reach a major number of possible interested authors, we will advertise the special issue as follows:
- The numerous national and international colleagues and contacts of the organizers will be contacted asking them to publicize the event. To this aim we will also exploit social networks and mailing lists. For example, we plan to create a project on Research Gate and an event both in Twitter and Facebook. Moreover, we plan to use for the advertisement mailing lists like DBbworld, SocInfo, European projects mailing lists.
- The several national and international partnerships of our CNR institute will be contacted to promote the event. Among which, University of Calabria, Polytechnic University of Turin, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, University of Manchester, University of Chicago, INRIA, University of Montpellier (LIRMM), University of Amsterdam, University of Cambridge, University of Oxford, IBM.
- A dedicated mailing list will be created to notify the call for papers of the special issue to all major researchers working on this research area.
Short CV of guest editors:
Carmela Comito is a researcher at the Institute of High Performance Computing and Networking of the Italian National Research Council (ICAR-CNR), and Adjunct Professor at University of Calabria, Italy. She received her Master’s degree in Computer Engineering and her Ph.D. in Systems and Computer Engineering from the University of Calabria, Italy. In 2006 she was a visiting researcher at the School of Computer Science of the University of Manchester, UK, and in 2017 she was a visiting researcher at LIRMM, University of Montpellier, France. She is adjunct professor at University of Calabria. She co-authored over 90 papers in international journals, conference proceedings, and edited volumes. She served as a chair, program committee member and reviewer of several international conferences and journals. She has been involved as both coordinator and participant in international and national research projects. Her research interests include artificial intelligence, big data analysis and mining, mobility mining, social network data analysis and mining, health informatics.
Shahab Shamshirband (Senior Member, IEEE) received the Ph.D. degree in computer science. He is an Associate Professor with the National Yunlin University of Science and Technology, Taiwan. He has published high-quality articles in refereed international SCI-IF journals with more than 13000 citations in Google Scholar. He has been listed among the top 1% of researchers by Thomson Reuters (Web of Science) based on the number of citations earned in the last three years. He was a Postdoctoral Research Fellow with the Data and Artificial Intelligence (DART) Group, Norwegian University of Science and Technology, Norway. He was a PI, Co-PI, expert, and machine learning specialist of various funded projects. He has served as a guest editor on the editorial board for journals. His major academic interests are in computational intelligence and data mining in multidisciplinary fields.
Ester Zumpano is an associate professor of Computer Engineering at the Department of Computer Engineering, Modeling, Electronics and Systems Engineering, University of Calabria (DIMES). She received a Phd in Computer Science from the University of Calabria in 2003. Her areas of research include health information systems, data integration, logic programming, view updating, distributed systems, artificial Intelligence, database management. She is member of the Scientific Board of the Ph.D. Course in Information and Communication Technologies, University of Calabria, Italy. She is a founding member of the ITACA S.r.l. spin-off. She participated in international, national and local research/technical projects. She has been member of judging commissions of the final exam for PhD students. She teaches undergraduate, graduate and PhD level courses in Computer Science at the University of Calabria since 2002. She served as a chair, program committee member and reviewer of several international conferences and journals.