Authors:
Anderson Almeida Firmino
1
;
Cláudio de Souza Baptista
1
;
André Luiz Firmino Alves
2
;
Davi Oliveira Serrano de Andrade
1
;
Hugo Feitosa de Figueirêdo
3
;
Geraldo Braz Filho
4
and
Anselmo Cardoso de Paiva
4
Affiliations:
1
University of Campina Grande, Brazil
;
2
University of Campina Grande and State University of Paraiba, Brazil
;
3
Federal Institute of Technology of Paraíba, Brazil
;
4
Federal University of Maranhão, Brazil
Keyword(s):
Opinion Mining, Sentiment Analysis, Tweets.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Data Mining
;
Databases and Information Systems Integration
;
Enterprise Information Systems
;
Natural Language Interfaces to Intelligent Systems
;
Sensor Networks
;
Signal Processing
;
Society, e-Business and e-Government
;
Soft Computing
;
Software Agents and Internet Computing
;
Web 2.0 and Social Networking Controls
;
Web Information Systems and Technologies
Abstract:
Recently, much research has been done in the area of sentiment analysis of microtexts, specially using tweets. In most studies, the sentiment polarity detection methods are solely based on textual information. The detection of opinionated content in texts is not a simple task, and even less simple in the context of social media. Furthermore, processing microtexts using just natural language techniques may lead to unsatisfactory results. There is a lack of works which link other properties of the tweets (metadata), such as retweets and likes, and the their opinion (i.e., the presence of sentiments). Using tweets collected during the 2013 FIFA Confederations Cup, which occurred in Brazil, this work proposes an analysis of metadata properties on tweets, in order to verify which of these properties have more impact on their opinionatedness. The results indicate that the properties “presence of links” and “retweets” are the most significant with respect to the opinionatedness of a tweet.