Public cognition of invasive alien species in China
Preprint
- 12 October 2025
- preprint
- Published by Springer Nature in Research Square
Abstract
Public understanding is critical for invasive alien species (IAS) management, yet national-scale cognition patterns remain understudied. We analyzed TikTok and Sina Microblog data to assess public cognition in China regarding three IAS: Solidago canadensis , Solenopsis invicta , and Trachemys scripta . Three dimensions of cognition, including focus (high-frequency terms), associations (term-pair linkages), and tendencies (sentiment polarity), were quantified using word frequency, semantic co-occurrence networks, and quantile-based sentiment analyses, respectively. Results revealed cross-species disparities: On TikTok, S. canadensis was concerned with its invasiveness (e.g., "Found everywhere", "Fertility → Overlord flower"), while Sina Microblog emphasized its agricultural utility (e.g., "Hu Sheep", "Digestion → Sheep dung"). S. invicta discussions centered on recognition/coping measures on TikTok (e.g., "Red fire ant", "Wound → Soapy water") versus ecological impacts on Sina Microblog (e.g., "Invasive species", "Consequence → Environment"), and T. scripta focused on pet raising issues (TikTok) (e.g., "My home", "Eyes → Can't open eyes") and regulatory policies (Sina Microblog) (e.g., "Release", "Heavy penalty → Country"). These disparities likely stem from species-specific traits and their interactions with human. Cross-platform differences were pronounced: TikTok’s experiential narratives showed polarized sentiment ( S. canadensis median = 0.63; lower/upper quartiles = 0.06/0.94), while Sina Microblog’s policy-driven discourse was predominantly positive (medians: 0.60–0.89). Algorithmic biases amplified these differences: prioritizing emotional content (TikTok) versus institutional narratives (Sina Microblog). A key gap was the scarcity of management strategies, limiting public engagement. Our findings advocate for platform-specific interventions (e.g., TikTok demos of removal techniques) and algorithmic transparency to improve IAS management.Keywords
All Related Versions
- Version 1, 2025-10-12, Research Square
- Published version: Biological Invasions, 28 (5), 111.
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