Semantics enabled role based sentiment analysis for drug abuse on social media: A framework

Abstract

With the advent of World Wide Web, social networking has evolved as a major driving force for communication and information sharing. Its usage has reinforced the concept of Six Degree of Separation in its true manner. Social media can be used for prediction, propagation, marketing and influencing purposes. The aim of this research is to present a comprehensive and novel framework that uses the social media to expedite the epidemiologic study and drug abuse. To achieve the aforesaid task a semantic web (SW) based model that enlightens itself with sentiment analysis (SA) is proposed with the amalgamation of role based (RB) ontological structure. The architecture not only evolves the drug abuse trends but also has the capability to suggest the stakeholders that how the drug addicts are influenced to curtail the illegitimate use of drugs. Ontology based role hierarchy calculates the influence factor of people around the drug abusers and suggests an appropriate personality that can influence the drug abuser to abstain from the drug abuse.