Paper Info
Title
A Lexicon approach to multidimensional analysis of tweets opinion
Abstract
Nowadays, social media present a valuable source for business decision support. This article outlines the integration of social opinion data in multidimensional design combining sentiment analysis techniques and ETL design to oifer a novel approach for social ETL design. The main contribution of this paper is the definition of a lexicon opinion analysis approach that extracts the sentiment polarity of informal text expressed in the Twitter social network. We propose a new algorithm, POLSentiment, based on lexical resources to firstly extract opinion words and emoticons from the tweet and then detect its positive or negative polarity. To assess the performance of the proposed algorithm, we evaluate POLSentiment on Sanders dataset. The results show that the proposal is suitable to automate the whole polarity analysis process, providing high accuracy levels and low false positive rates. Additionally, we define ETL processes design that consists of extracting tweets, its preprocessing, opinion analysis and polarity classification, then its loading into the Social Data Webhouse.
Year
DOI
Venue
2016
10.1109/AICCSA.2016.7945704
2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA)
Keywords
Field
DocType
opinion analysis,ETL design,Twitter,social media
Data mining,Social network,Computer science,Multidimensional analysis,Real-time computing,Natural language processing,Artificial intelligence,Social media,Algorithm design,Sentiment analysis,Decision support system,Preprocessor,Lexicon
Conference
ISSN
ISBN
Citations 
2161-5322
978-1-5090-4321-7
0
PageRank 
References 
Authors
0.34
11
3
Name
Order
Citations
PageRank
Afef Walha100.34
Faïza Ghozzi2118.61
Faïez Gargouri324492.29