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Public perceptions of mangroves: a sentiment and topic analysis of global Twitter/X content
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DOI：10.1080/26395916.2026.2650812.png)
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Abstract
En 中文
Social media has emerged as a prominent factor in shaping public perceptions. However, significant gaps remain in our understanding of the complex interplay between social media and human-nature relationships, including for mangrove ecosystems. We assessed how mangroves have been discussed and perceived on social media by analysing 649,495 Twitter/X posts between 2010 and 2022. Using NRC and AFINN lexicons, we found a prominence of positive sentiment toward mangroves across the 13‑year period. While negative sentiment was present, it was found to be co-occurring with degradation events (e.g. large dieback of mangroves in Australia in 2016). This indicates fear and anger were typically expressed for mangroves rather than of them. Topic mapping of the 100 most frequent bi-grams per year showed persistent topic structure despite fluctuations in volume. ‘Ecosystem Services’ was most prominent (14% of bi-gram frequencies), consisting of recreational and ecotourism terms (e.g. fishing, kayaking, boardwalks) and by coastal protection. Conversely, climate- and carbon related terms increasingly showcased policy relevant discourse. ‘Restoration’ was the second most frequent topic (13%) but was overwhelmingly framed as tree planting (64% of restoration bi-grams), revealing a simplified online narrative that overlooks context appropriate, holistic approaches. ‘Threats’ (11%) consists of tweets around widely covered events and includes sea level rise, pollution, aquaculture expansion, and general loss/destruction terms. Notably absent from top bi-grams were many provisioning and cultural services, as well as mangroves being social-ecological systems, highlighting perception gaps. Our findings demonstrate social media data can cost-effectively identify perception gaps and help inform (targeted) awareness campaigns.
Keywords:
Evangelia (Valia) Drakou
Mangroves
social media
sentiment analysis
ecology
public perception
text-mining
Journal
IF:
3.7
Papers:
314
Citations:
1.0K
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