Use of large web-based data to identify public interest and trends related to endangered species

Abstract

Use of the Internet by an increasing number of people to search for information related to varying disciplines has led to more precise data on societal views and trends. We used web search log data from a 6-year period and examined characteristics related to public interest in endangered species. Web search data for 246 endangered species as determined by the Ministry of Environment of Korea were evaluated. Relative search volumes for species were correlated with the status of conservation practices, and a self-organizing map (SOM) was used to analyze the relationship among selected variables. The relative search volume for higher taxa, including mammals, birds, amphibians and reptiles, were ten times higher than those for other taxa. SOM clusters were mainly divided according to the rank designation of the endangered species and the existence of a conservation facility dedicated to the species. The relative search volume and amount of web materials were the highest for the most highly ranked species. A positive relationship between the relative search volume and number of printed media articles (β 2.68; R 2 0.45; p < 0.0,001) and a negative relationship between the length of the common name of a species and number of printed media articles (β −125.7; R 2 0.48; p = 0.024) were found. The evaluation of endangered species by using web-based data can be useful to improve conservation tools, including using feedback to facilitate interaction among political, scientific, and socio-economic interests.

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Acknowledgments

This study was supported by the Korea National Long-Term Ecological Research (KNLTER) by the National Institute of Ecology, Ministry of Environment (S. Korea).

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Correspondence to Gea-Jae Joo.

Additional information

Communicated by Marcelo F Tognelli.

Appendix

Appendix

See Table 3.

Table 3 List of endangered species with their relative search volume, related  web materials, and printed media articles

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Kim, J.Y., Do, Y., Im, RY. et al. Use of large web-based data to identify public interest and trends related to endangered species. Biodivers Conserv 23, 2961–2984 (2014). https://doi.org/10.1007/s10531-014-0757-8

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Keywords

  • Internet
  • Relative search volume
  • Public interest
  • Trend
  • Self-organizing map