CLDec 5, 2023

Understanding Environmental Posts: Sentiment and Emotion Analysis of Social Media Data

arXiv:2312.03095v151 citationsh-index: 11IEEE Access
Originality Synthesis-oriented
AI Analysis

It provides insights into public sentiment on environmental issues for researchers and policymakers, but is incremental as it applies an existing method to new data.

This study analyzed public perception of climate change and the environment from 2014 to 2023 using social media data, finding that negative tweets are more common than positive or neutral ones, with key topics including climate change and air quality.

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 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 public reactions wide and complex nature. 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.

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