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<p>Invasion culturomics is an emerging field of study that utilizes digital data existing on the Internet to reveal the human dimensions of nonindigenous species (NIS). Although hypothetical approaches have been used to examine explanatory variables that predict the amount of public attention by using proxies, it has been difficult to observe direct associations between these variables. Here, by using the case study of NIS in Japan, we aimed to deepen our understanding of the relationship between people and NIS by analyzing the content of texts about NIS on social media, and by clarifying the context and aspects to which public attention is directed. Specifically, we quantified tweets about NIS to identify the most tweeted NIS that attract a lot of public attention on X/Twitter. We also identified topics in which NIS names occurred by applying topic modeling to tweets, and we investigated the topic distribution over the most tweeted NIS. 141 species were selected as the most tweeted NIS for further analysis, and 25 topics were identified from all the tweets used in the analysis. The topic distribution over the most tweeted NIS had three patterns across taxonomic groups: (1) biased among topics but consistent within taxonomic groups; (2) relatively even among topics and consistent within taxonomic groups; and (3) not consistent within taxonomic groups and with biases differing among species. These findings answer the question, “In what context, or in terms of what aspects, do NIS attract public attention?”, and provide insights into the formulation of better strategies for NIS management, particularly from the human and social perspectives.</p>

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Aspects of public attention on the most mentioned nonindigenous species, as determined by a comprehensive assessment of Japanese social media

  • 期刊论文

  • 发表日期：

    2025年1月10日

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  • Daiki Tomojiri,
  • Kosuke Takaya

摘要

Invasion culturomics is an emerging field of study that utilizes digital data existing on the Internet to reveal the human dimensions of nonindigenous species (NIS). Although hypothetical approaches have been used to examine explanatory variables that predict the amount of public attention by using proxies, it has been difficult to observe direct associations between these variables. Here, by using the case study of NIS in Japan, we aimed to deepen our understanding of the relationship between people and NIS by analyzing the content of texts about NIS on social media, and by clarifying the context and aspects to which public attention is directed. Specifically, we quantified tweets about NIS to identify the most tweeted NIS that attract a lot of public attention on X/Twitter. We also identified topics in which NIS names occurred by applying topic modeling to tweets, and we investigated the topic distribution over the most tweeted NIS. 141 species were selected as the most tweeted NIS for further analysis, and 25 topics were identified from all the tweets used in the analysis. The topic distribution over the most tweeted NIS had three patterns across taxonomic groups: (1) biased among topics but consistent within taxonomic groups; (2) relatively even among topics and consistent within taxonomic groups; and (3) not consistent within taxonomic groups and with biases differing among species. These findings answer the question, “In what context, or in terms of what aspects, do NIS attract public attention?”, and provide insights into the formulation of better strategies for NIS management, particularly from the human and social perspectives.