A Survey on Machine Learning Approaches to Social Media Analytics

摘要

Social networks have greatly influenced the usage pattern of Internet by common man. It has paved way for the great proliferation of Internet into the life of even the ordinary people. Such an exponential rise in the use of the world wide web due to social networks started to fetch huge volume of data across diverse domains in short period of time. These characteristics by which the huge amounts of social network data are generated make them to categorize as Big Data. Since the use of big data analytical techniques in many domains have obtained remarkable improvements in the way various businesses operate, we consider that social network domain is not an exception to this perception. Though there are many literatures available to deal with big data and social networks separately, only few papers deal with the analytical techniques of big data algorithms in the field of social networks. Hence, this paper will serve to act as a survey of big data analytical techniques as applied to social networks and efforts are taken appropriately to present the pros and cons of each algorithm. We also present the suggestions for use of various algorithms to various classes of social network data.