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Guest editorial: Recent Advances on Social Networking Analysis with Applications

Social networks have been one of the important issues in various domains, e.g., e-business and e-learning. In computer-based information systems, we have the possibility to process data about interactions and activities of millions of individuals. Communication and multiple user technologies allow us to form large networks which in turn shape and catalyze our activities. Due to scale, complexity and dynamics, these networks are extremely difficult to analyze in terms of traditional social network analysis methods. On the other hand, the data about human communication, common activities and collaboration simultaneously provide new opportunities for various social network applications.

So far, there have been the following contemporary publications related to social network analysis and social network applications.

- Social Networks (Elsevier)

- Sunbelt Social Networks Conference of the International Network for Social Network Analysis (INSNA)

With emerging interests in social networks (particularly, online social networks), we can find more opportunities for publishing in the following conferences and journals.

– Social Network Analysis and Mining

– International Journal of Social Network Mining

– Cyberpsychology, Behavior, and Social Networking

– International Journal of Virtual Communities and Social Networking

– IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)

– ASE/IEEE International Conference on Social Computing (SocialCom)

This special section is devoted to analysis of large-scale social structures and, what is more important, identification of the areas where social network analysis can be applied and provide the knowledge that is not accessible to other types of analyses. Additionally, applications of social networks analysis can be investigated either from static or dynamic perspectives. We seek business and industrial applications of social network analysis that help solve real-world problems. The area of social network analysis and its applications bring together researchers and practitioners from different fields and the main goal of this special section is to provide for these people the opportunity to share their visions, research achievements and solutions as well as to establish worldwide cooperative research and development. At the same time, we want to provide a platform for discussing research topics underlying the concepts of social network analysis and its applications by inviting members of different communities that share this common interest of investigating social networks.

The special section has selected 6 high-quality papers out of 21 submissions (about 28.6% acceptance rate). This was possible thanks to the work of the renowned researchers that provided their anonymous reviews.

The first paper in this section, authored by Dongjin Choi et al., proposes an interesting approach to discover who is isolated, why, and how the issue of social bullying can be addressed through an in-depth analysis of negative Tweets. For this, they have studied a web-based system for tracking events considered to be exciting by users and then analyzing the sentiment status of their Tweets.

The second paper authored by Grzegorz J. Nalepa and Szymon Bobek shows a new rule-based context reasoning platform tailored to the needs of intelligent distributed mobile computing devices. It contains a proposal of a learning middleware supporting context acquisition. The platform design is based on a critical review and evaluation of existing solutions.

In the third paper, Antonio Gonzalez-Pardo et al. present an e-learning platform by using virtual reality technologies and social network analysis. Using such virtual reality platform called VirtUAM, the information extracted from different experiments is used to analyze and define students communities based on their behavior.

The fourth paper by Duc Nguyen Trung and Jason J. Jung focuses on understanding customer’s feedback by analyzing how the information is diffused along social networks. It proposes fuzzy propagation modeling for opinion mining by sentiment analysis of online social networks. Thereby, a practical system, called TweetScope, has been implemented to efficiently collect and analyze all possible tweets from customers.

In the fifth paper, Rafeeque Pandara Chalil and Selvaraju Sendhilkumar present a novel framework based on sentiments and an algorithm to identify same wavelength groups from online social networks like Twitter. The proposed algorithm generates same wavelength groups in polynomial time for a relatively small set of events. The analysis of such groups would be of help in unraveling their response patterns and behavioral features.

The sixth paper by Namhee Lee et al. introduces a black-box evaluation framework of practical recommendation services. This work has designed a user modeling process for generating synthesized user models as the inputs for the recommendation services. This special section has been realized through a number of fruitful collaborations. We would like to thank the editor in chief of Computer Science and Information Systems (ComSIS), Mirjana Ivanović, for her kind support and help during the entire process of publication, and Yeungnam University Research Grant – 2013. Finally, we are most grateful to the authors for their valuable contributions and for their willingness and efforts to improve their papers in accordance with the reviewers’ suggestions and comments.

Guest Editor
Jason J. Jung