DocumentCode
660799
Title
A :) Is Worth a Thousand Words: How People Attach Sentiment to Emoticons and Words in Tweets
Author
Boia, Marina ; Faltings, B. ; Musat, Claudiu-Cristian ; Pu, Pearl
Author_Institution
Ecole Politechnique Fed. de Lausanne, Lausanne, Switzerland
fYear
2013
fDate
8-14 Sept. 2013
Firstpage
345
Lastpage
350
Abstract
Emoticons are widely used to express positive or negative sentiment on Twitter. We report on a study with live users to determine whether emoticons are used to merely emphasize the sentiment of tweets, or whether they are the main elements carrying the sentiment. We found that the sentiment of an emoticon is in substantial agreement with the sentiment of the entire tweet. Thus, emoticons are useful as predictors of tweet sentiment and should not be ignored in sentiment classification. However, the sentiment expressed by an emoticon agrees with the sentiment of the accompanying text only slightly better than random. Thus, using the text accompanying emoticons to train sentiment models is not likely to produce the best results, a fact that we show by comparing lexicons generated using emoticons with others generated using simple textual features.
Keywords
pattern classification; social networking (online); text analysis; Twitter; negative sentiment; positive sentiment; sentiment classification; sentiment models; text accompanying emoticons; textual features; tweet sentiment predictors; Dictionaries; Equations; Frequency estimation; Iterative methods; Semantics; Training; Twitter; Twitter; emoticons; sentiment classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Social Computing (SocialCom), 2013 International Conference on
Conference_Location
Alexandria, VA
Type
conf
DOI
10.1109/SocialCom.2013.54
Filename
6693351
Link To Document