Next Article in Journal
The Analysis of the Internet Development Based on the Complex Model of the Discursive Space
Next Article in Special Issue
Automata Approach to XML Data Indexing
Previous Article in Journal
Gene Selection for Microarray Cancer Data Classification by a Novel Rule-Based Algorithm
Previous Article in Special Issue
Source Code Documentation Generation Using Program Execution
Article Menu

Export Article

Open AccessArticle
Information 2018, 9(1), 1; https://doi.org/10.3390/info9010001

EmoSpell, a Morphological and Emotional Word Analyzer

CRACS & INESC-Porto LA, Faculty of Sciences, University of Porto, 4099-002 Porto Porto, Portugal
This paper is an extended version of our paper published in 6th Symposium on Languages, Applications and Technologies (SLATE 2017).
*
Author to whom correspondence should be addressed.
Received: 29 September 2017 / Revised: 26 November 2017 / Accepted: 7 December 2017 / Published: 3 January 2018
(This article belongs to the Special Issue Special Issues on Languages Processing)
Full-Text   |   PDF [1149 KB, uploaded 3 January 2018]   |  

Abstract

The analysis of sentiments, emotions, and opinions in texts is increasingly important in the current digital world. The existing lexicons with emotional annotations for the Portuguese language are oriented to polarities, classifying words as positive, negative, or neutral. To identify the emotional load intended by the author, it is necessary to also categorize the emotions expressed by individual words. EmoSpell is an extension of a morphological analyzer with semantic annotations of the emotional value of words. It uses Jspell as the morphological analyzer and a new dictionary with emotional annotations. This dictionary incorporates the lexical base EMOTAIX.PT, which classifies words based on three different levels of emotions—global, specific, and intermediate. This paper describes the generation of the EmoSpell dictionary using three sources: the Jspell Portuguese dictionary and the lexical bases EMOTAIX.PT and SentiLex-PT. Additionally, this paper details the Web application and Web service that exploit this dictionary. It also presents a validation of the proposed approach using a corpus of student texts with different emotional loads. The validation compares the analyses provided by EmoSpell with the mentioned emotional lexical bases on the ability to recognize emotional words and extract the dominant emotion from a text. View Full-Text
Keywords: sentiment analysis; opinion mining; Emotion API sentiment analysis; opinion mining; Emotion API
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Maia, M.I.; Leal, J.P. EmoSpell, a Morphological and Emotional Word Analyzer. Information 2018, 9, 1.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Information EISSN 2078-2489 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top