Paper Info
Title
A Comparison of SVM Versus Naive-Bayes Techniques for Sentiment Analysis in Tweets: A Case Study with the 2013 FIFA Confederations Cup
Abstract
The widespread of social communication media on the Web has made available a large volume of opinionated textual data stored in digital format. These media constitute a rich source for sentiment analysis and understanding of the opinions spontaneously expressed. Traditional techniques for sentiment analysis are based on POS Tagger. Considering the Portuguese language, the use of POS Tagging ends up being too costly, due to the complex grammatical structure of this language. Faced with this problem, a case study is carried out in order to compare two techniques for sentiment analysis: a SVM versus Naive-Bayes classifiers. Our study focused on tweets written in Portuguese during the 2013 FIFA Confederations Cup, although our technique could be applied to any other language. The achieved results indicated that the SVM technique surpassed the Naive-Bayes one, concerning performance issues.
Year
DOI
Venue
2014
10.1145/2664551.2664561
WebMedia
Keywords
Field
DocType
miscellaneous,analysis of sentiment,support vector machine,naive- bayes,data mining,natural language processing,naive bayes
Data mining,Naive Bayes classifier,Computer science,Sentiment analysis,Support vector machine,Portuguese,Social communication,Natural language processing,Artificial intelligence
Conference
Citations 
PageRank 
References 
7
0.52
21
Authors
5
Name
Order
Citations
PageRank
André Luiz Firmino Alves192.94
Cláudio de Souza Baptista213331.73
Anderson Almeida Firmino391.92
Maxwell Guimarães de Oliveira4247.15
Anselmo C. Paiva537948.88