Approaches to Cross-Domain Sentiment Analysis: A Systematic Literature Review - 2017 PROJECT TITLE : Approaches to Cross-Domain Sentiment Analysis: A Systematic Literature Review - 2017 ABSTRACT: A sentiment analysis has received a ton of attention from researchers operating within the fields of natural language processing and text mining. However, there's a scarcity of annotated information sets which will be used to coach a model for all domains, which is hampering the accuracy of sentiment analysis. Many research studies have tried to tackle this issue and to improve cross-domain sentiment classification. During this paper, we tend to gift the results of a comprehensive systematic literature review of the ways and techniques utilized in a cross-domain sentiment analysis. We have a tendency to specialize in studies printed during the period of 2010-2016. From our analysis of these works, it is clear that there is no good solution. Hence, one in all the aims of this review is to create a resource in the shape of an outline of the techniques, methods, and approaches that are used to try to solve the problem of cross-domain sentiment analysis in order to help researchers in developing new and additional accurate techniques in the future. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Event Detection and User Interest Discovering in Social Media Data Streams - 2017 Building and Querying an Enterprise Knowledge Graph - 2017