Sentiment Analysis of Sarcasm:

A Distributional Pattern of Sentiment Score within Sarcastic Tweets

Sarcasm has been a recent topic of research in linguistic discussion and computational application. In a broad definition, sarcasm expresses the opposite meaning of its form. The study of sarcasm often involves the discussion of its context and speakers' intention. For example, if a person says 'what a lovely weather' when it's clearly rainy and windy, the listeners would have to know what the weather is actually like in order to correctly interpret the comment as sarcastic. Clift [1] proposes that sarcasm is a type of irony and is distinct from irony in that the speaker is with intention to express hostile statement. Certain pragmatics goals are reached when speakers use these non-literal expressions. According to Brown and Levinson [2], using verbal irony can reduce threat and highlights shared knowledge among the interlocutors.

Clark and Gerrig [13] propose that a speaker expresses irony by pretending to be an injudicious person and expects the hearer to discover such pretense and recognize his attitude. In this study, we consider the use of degree adverbs as a clue of pretense in expressing sarcasm and examine this feature in terms of sentiment analysis.

summary(cars)
##      speed           dist    
##  Min.   : 4.0   Min.   :  2  
##  1st Qu.:12.0   1st Qu.: 26  
##  Median :15.0   Median : 36  
##  Mean   :15.4   Mean   : 43  
##  3rd Qu.:19.0   3rd Qu.: 56  
##  Max.   :25.0   Max.   :120

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