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.

Sentiment Analysis for the Natural Environment: a Systematic Review

Muhammad Okky Ibrohim
First
Membro del Collaboration Group
;
Cristina Bosco
Membro del Collaboration Group
;
Valerio Basile
Membro del Collaboration Group
2023-01-01

Abstract

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.
2023
Inglese
Esperti anonimi
56
4
1
37
37
https://dl.acm.org/doi/10.1145/3604605
Natural environment; data-driven policy; sentiment analysis; natural language processing (NLP); systematic review
no
1 – prodotto con file in versione Open Access (allegherò il file al passo 6 - Carica)
262
3
Muhammad Okky Ibrohim; Cristina Bosco; Valerio Basile
info:eu-repo/semantics/article
open
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1963530
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