Contemporary Gold Rush or Scientific Advancement: A Review of Social Network Analysis Approaches and Their Impact

Contemporary Gold Rush or Scientific Advancement: A Review of Social Network Analysis Approaches and Their Impact

Darren Quinn (University of Ulster, UK), Liming Chen (De Montfort University, UK) and Maurice Mulvenna (University of Ulster, UK)
DOI: 10.4018/978-1-4666-7284-0.ch013
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Following the expansion and mass adoption of Online Social Networks, the impact upon the domain of Social Network Analysis has been a rapid evolution in terms of approach, developing sophisticated methods to capture and understand individual and community interactions. This chapter provides a comprehensive review, examining state-of-the-art Social Network Analysis research and practices, highlighting key trends within the domain. In section 1, the authors examine the growing awareness concerning data as a marketable and scientific commodity. Section 2 reviews the context of Online Social Networking, highlighting key approaches for analysing Online Social Networks. In section 3, they consider modelling motivations of networks, discussing models in line with tie formation approaches. Section 4 outlines data collection approaches along with common structural properties observed in related literature. The authors discuss future directions and emerging approaches, notably semantic social networks and social interaction analysis before conclusions are provided.
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1. Introduction

In recent times the influence and value of data have been brought into sharp focus within both the public domain and the scientific community. Reports such as that of the hacking of Adobe systems in October 2013, where the data of more than 38 million users were acquired15, including encrypted passwords, names, debit and credit card numbers have now become a frequent incident, following on from a succession of high profile security breaches against targeted organisations. Commercially, the value of data is also being realised with the flotation of major Online Social Networking sites. In May 2012 the New York Stock Exchange (NYSE) valued Facebook at $104bn16 and more recently in November 2013 the flotation of Twitter valued the company at $18bn. To further underline the current focus on data, technology’s industry leaders are eager to understand its users behavioural patterns and interactions, and are highly sensitive to potential gains, describing it as the “the new oil”17. With such riches readily associated to user data, it creates the feel of a modern day gold rush for those aiming to comprehend and exploit data for both scientific and commercial advantage. However, understanding data and the behavioural patterns of users has evolved rapidly, particularly over the last decade within its scientific domain of Social Network Analysis (SNA).

The role of SNA is summarised as being to disclose how individuals and communities interact. As online technology evolved, advancements have meant that interactions which would have traditionally occurred face-to-face, now occur more frequently though Online Social Networks, facilitated by an array of social based platforms such as Twitter1, Facebook2 and Instgram3 etc. User adoption has exploded and in less than ten years Facebook amassed 1.19 billion users (Facebook Statistics, 2013) epitomising the rapid growth and adoption levels. Subsequently, interactions now occur on an unprecedented scale, with users generating billions of interactions on a daily basis in the form of tweets, instant messages and the sharing of photos etc. As such, exciting opportunities have arisen within SNA whereby communications can now be observed across the globe between all demographics.

However, the resulting challenge for SNA has been a rapid evolution in approach, in terms of how user interactions are captured and understood; interpreting the new insights gained from an expansion in the volume and mode of social interactions. Scientifically the domain has advanced significantly, particularly over the last decade, in-line with online and mobile technology. Increased interest in SNA is evidenced through the rising number of published articles on SNA. As illustrated in Figure 1, an explosion in domain popularity can be clearly observed from 2005 onwards where the number of articles began and has continued to rise year on year. This rise coincides directly with the commercialisation and mass adoption of social computing, with popularised social networking sites such as Facebook and Bebo4 which emerged in 2004 and 2005 respectively.

Figure 1.

Trending of published social network articles from 1995 to 2012


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