Title
Towards Metadata Analysis On Opinionated Content In Tweets
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.
Year
DOI
Venue
2016
10.5220/0005890803140320
PROCEEDINGS OF THE 18TH INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, VOL 2 (ICEIS)
Keywords
Field
DocType
Opinion Mining, Sentiment Analysis, Tweets
Data mining,Metadata,World Wide Web,Social media,Textual information,Sentiment analysis,Computer science,Natural language
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
7