Detecting changes in context using time series analysis of social network

Researchers are getting great benefits of big data as information gathered from social media like Facebook, Twitter are being used to perceive the lot from family planning to predicting postpartum depression. Detecting behavioral changes in social network represents an exciting new area of this progression that is used to counter organizational behavior and terrorism. Such analysis in social networks is categorized as dynamic data analysis. To process data dynamically time series considers as an essential component. This research proposes a novel technique that uses time series analysis in cyber space based social networks to detect variances or changes in human context overtime.