Analysis and Translation of English Sarcastic Text in Hindi

Sarcasm is a sardonic or bitter remark directed to show disrespect or ridicule. It has been used in Hindi since the decay of the language, and many Hindi idioms and proverbs use indirect sarcasm to intentionally comment on someone, such as “-”. Sentiment categorization is less difficult in comparison to sarcasm detection, as we see in the above-written idiom that it contains positive words with negative sentiment, but the meaning of the sentence represents that it is intended for a less educated person called knowledgeable in the group of foolish. In the reality of sarcasm, the originally intended meaning of the tweet written by the user is opposite to the literal meaning. Because of its intricate nature, it is much more difficult; similarly, without proper context, humans are not able to identify sarcasm in any verbal or textual sentence. Sarcasm detection in Hindi-language text is a challenging task in NLP due to the richness of morphology and low availability of resources. Hindi is spoken by 500 million people worldwide, and it's a very popular language. Twitter is the most widely used social networking platform and is substantially used by people to express views, feelings, and comments on recent issues in the form of tweets. On social media, the context of the tweets is often specified with the use of # (hashtags). In the context of the present paper, #sarcasm, #sarcastic, #kataksh, #, etc., will be used to access the sarcastic tweets in Hindi-English mixed code tweets, and then, we will analyze the tweets to detect sarcasm in text for sentiment analysis, opinion mining, etc., by using different machine learning algorithms. After that, we will apply the first-level machine translation to get the complete dataset into plain English-language text and next-level machine translation to achieve the Hindi-language text.