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Sentiment Analysis for the Natural Environment: A Systematic Review
In this systematic review, Kitchenham’s framework is used to explore what tasks, techniques, and benchmarks for Sentiment Analysis have been developed for addressing topics about the natural environment. We comprehensively analyze seven dimensions including contribution, topical focus, data source a...
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| Published in: | ACM computing surveys 2024-04, Vol.56 (4), p.1-37, Article 88 |
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| Main Authors: | , , |
| Format: | Article |
| Language: | English |
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| cited_by | cdi_FETCH-LOGICAL-a305t-fb3ada7aa986b988e58a1a496ad5aac7c50f89a8f87d37d1335df3c8647f064d3 |
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| cites | cdi_FETCH-LOGICAL-a305t-fb3ada7aa986b988e58a1a496ad5aac7c50f89a8f87d37d1335df3c8647f064d3 |
| container_end_page | 37 |
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| container_title | ACM computing surveys |
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| creator | Ibrohim, Muhammad Okky Bosco, Cristina Basile, Valerio |
| description | In this systematic review, Kitchenham’s framework is used to explore what tasks, techniques, and benchmarks for Sentiment Analysis have been developed for addressing topics about the natural environment. We comprehensively analyze seven dimensions including contribution, topical focus, data source and query, annotation, language, detail of the task, and technology/algorithm used. By showing how this research area has grown during the last few years, our investigation provides important findings about the results achieved and the challenges that need to be still addressed for making this technology actually helpful for stakeholders such as policymakers and governments. |
| doi_str_mv | 10.1145/3604605 |
| format | article |
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| fulltext | fulltext |
| identifier | ISSN: 0360-0300 |
| ispartof | ACM computing surveys, 2024-04, Vol.56 (4), p.1-37, Article 88 |
| issn | 0360-0300 1557-7341 |
| language | eng |
| recordid | cdi_proquest_journals_3031366820 |
| source | Business Source Ultimate; Association for Computing Machinery:Jisc Collections:ACM OPEN Journals 2023-2025 (reading list) |
| subjects | Algorithms Annotations Computer science Computing methodologies Data mining Natural language processing Query languages Sentiment analysis |
| title | Sentiment Analysis for the Natural Environment: A Systematic Review |
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