Implementation of a Sentiment Analysis Platform for Opinion Mining of Social Media Texts

Abstract

This study aims to introduce DecoTex, a language resource-based sentiment analysis platform, implemented for opinion mining of social media texts. DecoTex supports several functions such as the Twitter crawler, Preprocessing module, and Sentiment Analysis modules. The Sentiment Analysis modules consist of two parts: Supervised Machine Learning options requiring Sentiment- Annotated Corpora as training data and Lexicon-based algorithmic options based on Sentiment Lexica and Local Grammars. By illustrating a process of classifying positive/negative opinions on ‘China’ and ‘Japan’ in Twitter texts through DecoTex platform, this study emphasizes the importance of a computational platform for humanities researchers. We believe that it is crucial to free them from making efforts to learn programming skills for obtaining experimental results or evaluating their studies since they may focus on constructing linguistic resources that require an enormous amount of time, energy, and knowledge.