Machine Learning Based Social Big Data Mining for Communal Welfare

Abstract

With the evolution of social web, various networking services have contributed towards the establishment of a powerful platform that allows interaction and communication among people across the globe through shared information and messages. Unlike the traditional internet (which only supported one way communication) users can now not only gain information, but can also spread information using social media. This large amount of unstructured and freely available content posted by millions of internet users can be exploited to gain insight into various domains such as government strategies and ventures, marketing and research, business process optimization, smart society services etc. Several computational intelligence techniques are available to provide assistance in analyzing this huge content by means of big data analytics. Sentiment analysis is a pivotal intelligent learning technique which can be used to evaluate the public response to any topic, event, phenomenon, decision, or issue. An effective and suitable process of sentiment analysis leads to appraisal of an organization or governing body’s project as per the general opinion of the public. The goal of this paper is to assess one of the most recent government initiatives, i.e. Chief Minister’s Distress Relief Fund (CMDRF), launched with an objective of rebuilding Kerala after the massive floods faced by the state. CMDRF is an open platform for people to come out and donate money for Kerala’s flood affected victims. This paper is an attempt to analyze the public discernment of this initiative using intelligent learning algorithms to comprehend the positive and negative impression of the project. The social media platform Twitter has been used extensively for eliciting and extracting public views or reactions over this initiative.