Login / Signup

A Google Trends Analysis of Interest in Nonbinary Identities.

Madeleine R HollandLee Ann Kahlor
Published in: Cyberpsychology, behavior and social networking (2023)
Emerging research on stigma suggests that society's mistreatment of nonbinary individuals can, in part, be attributed to public uncertainty and a lack of knowledge about nonbinary identities. In response to this, this study drew upon the theoretical framework of uncertainty management to explore research questions related to nonbinary identity and information behaviors by investigating uncertainty management as evidenced by longitudinal Google Trends data related to nonbinary gender identities. If individuals were found to be engaging in information seeking, the result of this behavior may be that they become less likely to hold stigmatizing attitudes toward nonbinary people, and ultimately be less likely to engage in discrimination toward them. Results indicated that indeed there has been an increase in search volume interest related to nonbinary identities in the past decade. The study concludes by presenting the need for further research to clarify the nature of the relationship between stigma and information seeking, as well as presenting a quandary for researchers regarding the desire for more detailed demographic data, as balanced with concerns for privacy.
Keyphrases
  • mental health
  • health information
  • big data
  • healthcare
  • electronic health record
  • social media
  • cross sectional
  • social support
  • depressive symptoms
  • machine learning
  • case report
  • deep learning
  • hiv infected
  • adverse drug