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AI-ML Based Sentiment Analysis: a Review

EasyChair Preprint no. 9697

9 pagesDate: February 14, 2023


The primary software of herbal language processing is to analyse the author's sentiment via context. This sentiment evaluation (SA) is said to determine the exactness of the underlying emotion in the context. it's been used in a variety of fields, inclusive of inventory market forecasting, social media statistics on product evaluations, psychology, judiciary, forecasting, disorder prediction, agriculture, and so on. Many researchers have laboured in these areas and have produced considerable outcomes. those effects are useful of their respective fields because they help to apprehend the general precis in a brief quantity of time. furthermore, Sentiment evaluation aids in comprehending actual remarks shared throughout numerous structures including Amazon, TripAdvisor, and others. The number one purpose of this significant survey changed into to examine a number of the maximum critical research. carried out thus far, in addition to offer an overview of Sentiment analysis fashions within the field of emotion AI-driven SA. moreover, this work discusses Sentiment analysis on various varieties of data along with snap shots and speech. visible Sentiment analysis seeks to recognize how snap shots have an effect on humans in phrases of evoked emotions. no matter the fact that this area is distinctly new, a wide range of strategies for numerous information assets and issues were advanced, resulting in a considerable frame of studies. To that end, this paper considers a  dependent formalisation of the problem that is commonly used for textual content evaluation and discusses its applicability inside the context of visual Sentiment evaluation. an outline of recent challenges is likewise blanketed inside the paper, the evaluation from the perspective of progress toward extra state-of-the-art structures and related practical applications, as well as a precis of the insights as a result of this observe.

Keyphrases: Emotion AI, machine learning, multi-lingual, neural networks, Sentiment Analysis, Visual Sentiment Analysis

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Arya Bharadwaj and Anjali Awasthi and Aviral Singh and Abhisakshi Srivastava and Abhishek Mishra and Ayushi Tiwari},
  title = {AI-ML Based Sentiment Analysis: a Review},
  howpublished = {EasyChair Preprint no. 9697},

  year = {EasyChair, 2023}}
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