Feature based Composite Approach for Sarcasm Detection using MapReduce

Sarcasm is defined as witty language used to convey insults or scorn. It is utilized for remarks that obviously mean the opposite individuals need to state, made keeping in mind the end goal to offend someone or to reprimand something hilariously. While speaking, it is very easy to distinguish sarcasm utilizing pitch of voice, gesture, facial expression etc. But in textual data, it is difficult to detect sarcasm due to lack of described factors. Sentimental analysis is used to know someone's opinion, attitude towards particular event, company etc. Sarcasm is one type of person's sentiment but used for taunting, insulting, to make fun of someone. Various algorithms are proposed to detect sarcasm based on different features, domains and type of sarcasm. We used a Hadoop based framework that utilized live tweets, process it and use hybrid algorithm which identifies sarcastic sentiment efficiently. Hybrid approach consider lexical and hyperbole feature to improve performance of system by increasing accuracy, precision, F-score.