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Sentiment Analysis in Digital Spaces: An Overview of Reviews

arXiv 2310.19687 ↗First posted 30 Oct 2023cs.CY cs.CLcited by 0

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Abstract (arXiv)

Sentiment analysis (SA) is commonly applied to digital textual data, revealing insight into opinions and feelings. Many systematic reviews have summarized existing work, but often overlook discussions of validity and scientific practices. Here, we present an overview of reviews, synthesizing 38 systematic reviews, containing 2,275 primary studies. We devise a bespoke quality assessment framework designed to assess the rigor and quality of systematic review methodologies and reporting standards. Our findings show diverse applications and methods, limited reporting rigor, and challenges over time. We discuss how future research and practitioners can address these issues and highlight their importance across numerous applications.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 29 of its 213 references that are in the map. First posted on arXiv 30 Oct 2023.

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29 of 213 references.

References · 29

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17 more
  1. 2020Beneath the Tip of the Iceberg: Current Challenges and New Directions in Sentiment Analysis Researchcited by 67
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  3. 2016Sentiment Analysis of Twitter Data for Predicting Stock Market Movementscited by 34
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  7. 2016The Evolution of Sentiment Analysis - A Review of Research Topics, Venues, and Top Cited Paperscited by 20
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  15. 2020A systematic literature review on machine learning applications for consumer sentiment analysis using online reviewscited by 5
  16. 2019Natural Language Processing, Sentiment Analysis and Clinical Analyticscited by 4
  17. 2021Towards transparency in NLP shared taskscited by 3

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