General Purpose Textual Sentiment Analysis and Emotion Detection Tools

TL;DR

This paper introduces general-purpose tools for textual sentiment analysis and emotion detection, addressing theoretical and practical challenges to enable broad applicability across domains and languages.

Contribution

It presents novel sentiment and emotion analysis tools along with strategies to overcome domain and language dependence issues.

Findings

Tools demonstrate high accuracy across multiple domains

Effective handling of cross-lingual sentiment detection

Applications include opinion mining and feedback analysis

Abstract

Textual sentiment analysis and emotion detection consists in retrieving the sentiment or emotion carried by a text or document. This task can be useful in many domains: opinion mining, prediction, feedbacks, etc. However, building a general purpose tool for doing sentiment analysis and emotion detection raises a number of issues, theoretical issues like the dependence to the domain or to the language but also pratical issues like the emotion representation for interoperability. In this paper we present our sentiment/emotion analysis tools, the way we propose to circumvent the di culties and the applications they are used for.