State-of-the-art methods for sentiment prediction
Abstract
Social media sentiment analysis has become a trendy issue recently. It is used and supported by numerous organizations across many industries due to its useful applications. To obtain insights, marketers are keen to hear what customers have to say. The difficulties in acquiring, deciphering, and extracting useful information from the vast amount of data that is constantly generated have multiplied. Crunching social data is still difficult, despite advances in technology and increased computational power. This well-organized study is devoted to comprehending the current state of sentiment analysis as a whole, including typical techniques, gaps, and methodologies. This study uses a logical approach to find, acquire empirical data, critically evaluate, and integrate the findings of all relevant to respond to certain research questions about the specified research topic. Additionally, this research defines the various sentiment analysis types and methods. This study holds its significance in light of these two contributions.
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