This Thematic Series of the Journal of Internet Services and Applications (JISA) presents a collection of articles around the topic of Social Network Analysis and Mining (SNAM). From advances in Computer Science research and practice, the field of SNAM has become an important subject due to (i) the large amount and diversity of data that could be analyzed, (ii) the capacity of processing and solving complex analysis with efficiency, (iii) the development of new solutions for visualization of complex networks, and (iv) the application of SNAM concepts in different domains.
The study of social networks was leveraged by the social, educational and business communities. Academic interest in this field has been growing since the mid twentieth century , given the increasing interaction among people, data dissemination and exchange of information. In this scenario, big data sets require more accurate analyses. As such, the development and evaluation of new techniques for social network analysis and mining (SNAM) is a current key research area for Internet services and applications. These topics have important areas of application in a wide range of fields.
A social network is composed of actors who have relationships with each other. Networks can have a few to many actors (nodes) and one or many types of relationships (arrows) between pairs of actors . In our daily life, we have several practical examples of social networks: our family, friends, and colleagues from the university, gym, work, or casual meetings. Individuals and organizations – seen as nodes in social networks – can be connected due to several reasons, such as friendship and genealogy, but also values, visions, ideas, finances, disagreements, conflicts, services, computer networks, air routes etc. The structure created from such a large amount of relationships is complex. Therefore, researchers study the network as a whole from a sociocentric view (all the links referring to specific relations in a given population), or as a social structure in an egocentric view (with links selected from specific people) .
In addition, people join and create groups in any society , but the web platform fostered critical changes in the way people can interact and think about the reality. Interactions (i) become easier, (ii) allow a frequent exchange of information, and (iii) transform communications tools and social media (e.g., microblogs, blogs, wikis, Facebook) to mass communication means that are more agile and far-reaching. As such, the use of social media contributes to the sharing of different types of information, especially in real time. Some examples are personal data, location, opinions and preferences. In this context, SNAM can support the understanding of preferences and associations, the identification of interactions, the recognition of influences, and the comprehension of information flow (context and concepts) among network actors.
Finally, the understanding of interactions in a specific scenario can produce concrete results. In an organization, employees should work to avoid problems regarding knowledge sharing . In natural science, social networks can aid in the study of endemies and epidemies propagation . In marketing, SNAM can be used as a tool for brand spread, or for the study of a market segment towards the understanding of how information propagates . The last (but not least) example is the use of SNAM for the identification of criminal networks .
This JISA Thematic Series originates from the 6th Brazilian Workshop on Social Network Analysis and Mining (BraSNAM 2017) that was held in São Paulo, Brazil, on July 04–05, 2017. BraSNAM 2017 was affiliated with the 37th Brazilian Computer Society Congress (CSBC 2017) which is the official event of the Brazilian Computer Society (SBC). BraSNAM is focused on bringing together researchers and professionals interested in social networks and related fields. The workshop aims at providing innovative contributions to the research, development and evaluation of novel techniques for SNAM and applications. Finally, the main goal is to provide a valuable opportunity for multidisciplinary groups to meet and engage in discussions on SNAM.
Continuing in this direction, this JISA Thematic Series targets new techniques for the field of SNAM, mainly fostered by the context of Internet services and applications. We received contributions at various levels: from theoretical foundations to experiments and case studies based on real cases and applications; from modeling to mining and analysis of big data sets; and from different subjects and domains, such as entertainment, public transportation, elections, and personal social circles.
This Thematic Series presents high-quality research and technical contributions. We received six submissions as extended versions of the best papers of BraSNAM 2017. Topics included: analysis of online discussion and comments, complex networks, graph mining, government open data, power metrics, community detection, link assessment, homophily, and sentiment analysis. The five out of six submissions that were selected for publication and appear in this issue are summarized in the following section.