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Welcome to the second issue of the Social Network Analysis and Mining journal. In this issue, we will continue to demonstrate the high standard of the SNAM journal which started by publishing five well written papers in the first issue. We are delighted to witness the journal gaining popularity since the first articles were published online. The number of visitors to the online version of the journal is increasing rapidly and the number of downloaded articles shows the interest in the journal. We much appreciate the increased interest in the journal. We are receiving more submissions than expected. Fortunately, we are maintaining the short turnaround time for the reviewing process; humble thank you to the expert reviewers and board members who dedicate their valuable time and effort to submit timely detailed and constructive reports. Readers of this issue will enjoy the research achievements reported mostly by computer scientists who are experts in social network analysis and mining. This shows how the research in social networks has attracted considerable attention outside the basic disciplines where it originated, i.e., sociology and anthropology. We witness the application of the social network methodology in variety of disciplines. Market basket analysis is one good application covered in this issue. It is even hard to think of a discipline which cannot benefit from the richness of the social network methodology. The social network methodology has been well received in the scientific community due to several reasons, including the strong foundations in science and the tremendous development in the information technology. Basic sciences influenced the social network methodology from data collection, to network construction, to network dynamics, to network analysis, to results interpretation, etc. Good background in graph theory, linear algebra and statistics is necessary for successful application of the social network methodology. On the other hand, the development in information technology allowed researchers to consider scalability of the analyzed social networks. Automating the analysis and the sophisticated computing infrastructure and methods have direct influence on the successful research in network dynamics at large. Further, the development of Web 2.0, web services and web semantics has produced the current popularity of the terms ‘‘online social networks’’ and ‘‘social media’’. People are heavily involved in online social networks without knowing how they are structured or evolve. The first paper in this issue describes a novel method for analyzing online friendship networks. We decided to have the SNAM journal open to both technical and non-technical articles in order to cover the multidisciplinary nature of the research and hence help in meeting the expectations of the wide spectrum of readers, including both researchers and practitioners. Though the papers in this issue are mainly written by computer scientists, we have already accepted some other less technical articles, some of which have appeared in the first issue and others will be included in future issues. The current issue contains five well written papers covering various aspects of social networks analysis and R. Alhajj (&) Department of Computer Science, University of Calgary, Calgary AB T2N 1N4, Canada e-mail: alhajj@ucalgary.ca; rsalhajj@gmail.com

Introduction to the second issue of Social Network Analysis and Mining journal: scientific computing for social network analysis and dynamicity