Public Opinion Mining in Social Network and Media

Opinion mining is a method of requesting and processing opinions expressed in open sources such as social media. There are such reactions as the discussion of the topics vital to the current period of time, discussion of events and positions. Opinion mining approach applies uses such tools as natural language processing (NLP) that are targeted at the identification of the level and type of sentiment about a certain domain or subject and the clarification of text polarity. The modern world provides a wide range of social media sources in which opinions are shared openly. Therefore, these sources can be used for the understanding of the global positions to the domains in certain social spheres. The goal of this research is to produce the analysis of the opinion mining approaches and to apply the most known and state of art NLP methods to look into feminism according to various social media sources and public networks. Moreover, this paper proposes the overall forecast on the possible trends in the opinions about feminism using the recent personal data of users. Besides, this research includes an overview of the key issues, difficulties, and methods of texts polarity classification and processing. The document provides the context of the existing researches on the social media phenomenon using opinion mining, explains the ground difficulties of text pre-processing in terms of social networks, lists approaches for the polarity analysis, and describes the current research thesis statement.