Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: People express their opinions about things like products, celebrities and services using social media channels. The analysis of these textual contents for sentiments is a gold mine for marketing experts as ll as for research in humanities, thus automatic sentiment analysis is a popular area of applied artificial intelligence. The chief objective of this paper is to investigate automatic sentiment analysis on social media contents over various text sources and languages. The comparative findings of the investigation may give useful insights to artificial intelligence researchers who develop sentiment analyzers for a new textual source. To achieve this,  describe supervised machine learning based systems which perform sentiment analysis and  comparatively evaluate them on seven publicly available English and Hungarian databases, which contain text documents taken from Twitter and product review sites.  discuss the differences among these text genres and languages in terms of document- and target-level sentiment analysis.
['Viktor Hangya', 'Richárd Farkas']
I am writing a research paper on a idea A comparative empirical study on social media sentiment analysis over various genres and languages
[{"from": "human", "value": "I am writing a research paper on a idea A comparative empirical study on social media sentiment analysis over various genres and languages"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: People express their opinions about things like products, celebrities and services using social media channels. The analysis of these textual contents for sentiments is a gold mine for marketing experts as ll as for research in humanities, thus automatic sentiment analysis is a popular area of applied artificial intelligence. The chief objective of this paper is to investigate automatic sentiment analysis on social media contents over various text sources and languages. The comparative findings of the investigation may give useful insights to artificial intelligence researchers who develop sentiment analyzers for a new textual source. To achieve this,  describe supervised machine learning based systems which perform sentiment analysis and  comparatively evaluate them on seven publicly available English and Hungarian databases, which contain text documents taken from Twitter and product review sites.  discuss the differences among these text genres and languages in terms of document- and target-level sentiment analysis."}]