Background to Social Network Analytics.
Social Network Analysis (SNA) has its beginnings in the latter half of the 20th century, originating out of a number of sociological and anthropological studies of relatively small groups of people. Initially, the selection of small social networks was driven by the difficulty in manually collecting data, using direct observations or surveys of the people comprising the study group. However, even with the limited data collection and processing capabilities of the time, sociologists such as J.A. Barnes and Mark Granovetter managed to study group behaviour, and derive some interesting findings on how people behave within a network of their peers. Further evaluations of social networks were limited by the amount of effort required to design, implement and measure communication patterns between changing groups of people. Survey-driven analysis, as well as direct observation could only provide a limited snapshot of group behaviour, whereas manual tabulation of results was constrained by the time and resources available to the researchers. Luckily, the need to record and process complex social networks coincided with an increase in the processing capabilities of computer systems in early 1970s, and a corresponding decrease in their cost. Suddenly, the prospect of calculating multiple social network metrics for large groups of people became tractable, and cost-effective.
Today, the analysis of social networks containing many millions of actors has become possible, enabling Idiro to predict the behaviour of individuals within the context of a much larger group. In addition, using complex graph partitioning algorithms, we can break a very large network into communities of closely linked individuals, such as friends, business colleagues and families. Using our state-of-the-art visualization tools, Idiro provides its customers with both a macro and micro-level view of the predicted behaviour of social networks based on their previous history. Having come from time-consuming punch-card driven processing of the 1960s to real-time cloud-based analysis of the present, the future of Social Network Analysis lies in an ever greater understanding of the complex forces that shape our behaviour, preferences and lifestyle.