Understanding Environmental Posts: Sentiment and Emotion Analysis of Social Media Data
Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet
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in: IEEE Access, Jahrgang 12, 07.03.2024, S. 33504-33523.
Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet
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RIS
TY - JOUR
T1 - Understanding Environmental Posts
T2 - Sentiment and Emotion Analysis of Social Media Data
AU - Amangeldi, Daniyar
AU - Usmanova, Aida
AU - Shamoi, Pakizar
N1 - Publisher Copyright: © 2013 IEEE.
PY - 2024/3/7
Y1 - 2024/3/7
N2 - Social media is now the predominant source of information due to the availability of immediate public response. As a result, social media data has become a valuable resource for comprehending public sentiments. Studies have shown that it can amplify ideas and influence public sentiments. This study analyzes the public perception of climate change and the environment over a decade from 2014 to 2023. Using the Pointwise Mutual Information (PMI) algorithm, we identify sentiment and explore prevailing emotions expressed within environmental tweets across various social media platforms, namely Twitter, Reddit, and YouTube. Accuracy on a human-annotated dataset was 0.65, higher than Vader's score but lower than that of an expert rater (0.90). Our findings suggest that negative environmental tweets are far more common than positive or neutral ones. Climate change, air quality, emissions, plastic, and recycling are the most discussed topics on all social media platforms, highlighting its huge global concern. The most common emotions in environmental tweets are fear, trust, and anticipation, demonstrating the wide and complex nature of public reactions. By identifying patterns and trends in opinions related to the environment, we hope to provide insights that can help raise awareness regarding environmental issues, inform the development of interventions, and adapt further actions to meet environmental challenges.
AB - Social media is now the predominant source of information due to the availability of immediate public response. As a result, social media data has become a valuable resource for comprehending public sentiments. Studies have shown that it can amplify ideas and influence public sentiments. This study analyzes the public perception of climate change and the environment over a decade from 2014 to 2023. Using the Pointwise Mutual Information (PMI) algorithm, we identify sentiment and explore prevailing emotions expressed within environmental tweets across various social media platforms, namely Twitter, Reddit, and YouTube. Accuracy on a human-annotated dataset was 0.65, higher than Vader's score but lower than that of an expert rater (0.90). Our findings suggest that negative environmental tweets are far more common than positive or neutral ones. Climate change, air quality, emissions, plastic, and recycling are the most discussed topics on all social media platforms, highlighting its huge global concern. The most common emotions in environmental tweets are fear, trust, and anticipation, demonstrating the wide and complex nature of public reactions. By identifying patterns and trends in opinions related to the environment, we hope to provide insights that can help raise awareness regarding environmental issues, inform the development of interventions, and adapt further actions to meet environmental challenges.
KW - climate change
KW - emotion analysis
KW - global warming
KW - pointwise mutual information
KW - public perception
KW - Reddit
KW - Sentiment analysis
KW - social media
KW - Twitter
KW - YouTube
KW - Informatics
KW - Business informatics
UR - http://www.scopus.com/inward/record.url?scp=85187023491&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2024.3371585
DO - 10.1109/ACCESS.2024.3371585
M3 - Journal articles
AN - SCOPUS:85187023491
VL - 12
SP - 33504
EP - 33523
JO - IEEE Access
JF - IEEE Access
SN - 2169-3536
ER -