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A Systematic Review of Social Network Sentiment Analysis with Comparative Study of Ensemble-based Techniques by Dimple Tiwari; Bharti Nagpal; Bhoopesh Singh Bhati; Ashutosh Mishra; Manoj Kumar is a Computer Science article available to read on EtoBox.

What is A Systematic Review of Social Network Sentiment Analysis with Comparative Study of Ensemble-based Techniques about?

Sentiment Analysis (SA) of text reviews is an emerging concern in Natural Language Processing (NLP). It is a broadly active method for analyzing and extracting opinions from text using individual or ensemble learning techniques. This field has unquestionable potential in the digital world and social media platforms. Therefore, we present a systematic survey that organizes and describes the current scenario of the SA and provides a structured overview of proposed approaches from traditional to advance. This work also discusses the SA-related challenges, feature engineering techniques, benchmark datasets, popular publication platforms, and best algorithms to advance the automatic SA. Furthermore, a comparative study has been conducted to assess the performance of bagging and boosting-based ensemble techniques for social network SA. Bagging and Boosting are two major approaches of ensemble learning that contain various ensemble algorithms to classify sentiment polarity. Recent studies recommend that ensemble learning techniques have the potential of applicability for sentiment classification. This analytical study examines the bagging and boosting-based ensemble techniques on four ben

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Author

Dimple Tiwari; Bharti Nagpal; Bhoopesh Singh Bhati; Ashutosh Mishra; Manoj Kumar

Publisher

Springer Science and Business Media LLC

Published

2023

Language

EN

Field

Computer Science (Physical Sciences)