We are now standing on the top of a new wave of information revolution. Everything on the Internet have been gradually combine d together. The introduction of Siri has revealed the true power of artificial intelligence, the emergence of semantic search engine has indicated the start of the evolution from Web 2.0 to Web 3.0, all these current developments of information technologies, without any exception, have shared the same target, "make our computer and network more intelligent". But how? The first step is to let ourselves be truly understood by the computer. This is also the basic goal of Social Network Analysis.
Social Network Analysis is the study of social relations among a set of actors. The essential difference between network analysis and other approaches to social science is the focus on relationships between actors rather than the attributes of individual actors. Social analysis takes a global view on the whole social structures based on the belief that different patterns of relationships emerge from individual connectivity and that the presence of such patterns have substantial effects on the network and its members. In particular, the network structures and patterns provide us opportunities to understand, calculate or even forecast some certain behaviors in a computational way.
However, although the target of Social Network Analysis is quite easy to be understood, its utilization in real life situation is still remain vague for most of people. Here I will introduce a real case to illustrate the value of Social Network Analysis. It is called "Early Warning Social Listening".
In daily lives, we have to frequently confront the disasters brought by both nature and human being, for example epidemics is one of the most detrimentals. However, even though we are always keeping in mind the necessity to control it as soon as possible, the result of our emergency measures is always not as good as we have expected. It's usually too late for us to realize the emergence of that kind of disaster. Once noticed, the infection usually has taken hold in a sizable proportion of the population and is spreading at geometric rates. The right time for crises prevention has passed, and all of our responding actions have been forced into a passive way.
Could we find a better approach to get the warning earlier? The method could come from Social Network Analysis. In a study of Harvard undergraduateds, Christakis and Fowler, two scientists in the field of social network science, have predicted the outbreak of the H1N1 influenza virus on campus in 2009 after analyzing the unusual behavior patterns among the social network. During the analysis, they found that fact that there were an increasing number of initially active nodes become reticence in a short period of time and at the same time many "stranger" nodes get new connection to these certain group of nodes. And finally, with a further investment, they found the reason of this usual pattern and effectively avoid a disaster.
Up till now, the SNA has still remained in an early stage. Do you have any ideas about the SNA's utilization in real life situation? Expecting for your response.
