A Compendium of Classification Techniques, Tools and Evaluation Datasets for Twitter Sentiment Analysis

Abstract

Social networking sites and micro blogs provide tremendous amount of real time data every day. Sentiment analysis or opinion mining aims to automate the process of sentiment extraction from the user content available online. Twitter in recent years due to its high subscriber rate and diverse audience, has become increasingly powerful in representing and changing user opinions over an object or event. This paper focuses on research conducted within the field of twitter sentiment analysis. The objective is to comprehensively investigate the task of sentiment analysis and its sub processes and identify the different tools, techniques or other resources used or applied on twitter data during the process. A Systematic Literature Review (SLR) has been conducted to identify 40 researches, relevant to sentiment identification and analysis. The work presented covers major tools and techniques used during sentiment mining process and maybe utilized by researchers or practitioners for identifying potential research directions as well as suggest possible software development areas that need to be explored.