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Regional Differences in Information Privacy Concerns After the Facebook-Cambridge Analytica Data Scandal

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Springer, London

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While there is increasing global attention to data privacy, most of their current theoretical understanding is based on research conducted in a few countries. Prior work argues that people’s cultural backgrounds might shape their privacy concerns; thus, we could expect people from different world regions to conceptualize them in diverse ways. We collected and analyzed a large-scale dataset of tweets about the #CambridgeAnalytica scandal in Spanish and English to start exploring this hypothesis. We employed word embeddings and qualitative analysis to identify which information privacy concerns are present and characterize language and regional differences in emphasis on these concerns. Our results suggest that related concepts, such as regulations, can be added to current information privacy frameworks. We also observe a greater emphasis on data collection in English than in Spanish. Additionally, data from North America exhibits a narrower focus on awareness compared to other regions under study. Our results call for more diverse sources of data and nuanced analysis of data privacy concerns around the globe.

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González-Pizarro, Felipe; Figueroa, Andrea; López, Claudia; Aragon, Cecilia (2022): Regional Differences in Information Privacy Concerns After the Facebook-Cambridge Analytica Data Scandal. Computer Supported Cooperative Work, Vol. 31. DOI: 10.1007/s10606-021-09422-3. Springer, London. PISSN: 0925-9724. pp. 33–77. Full Papers

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Online privacy, Twitter, Word embedding, Content analysis, IUIPC

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Number of citations to item: 5

  • William Agnew, A. Stevie Bergman, Jennifer Chien, Mark Díaz, Seliem El-Sayed, Jaylen Pittman, Shakir Mohamed, Kevin R. McKee (2024): The Illusion of Artificial Inclusion, In: Proceedings of the CHI Conference on Human Factors in Computing Systems, doi:10.1145/3613904.3642703
  • Naufil Kazi, Deepa Parasar, S. Sangita Mishra (2023): Importance of varied databases in machine learning, In: AIP Conference Proceedings, doi:10.1063/5.0149707
  • George Balabanis, Anastasia Stathopoulou, John Balabanis (2024): Cultural Influences on Privacy Calculus in Loyalty Programs: An Analysis of Individual and National-Level Cultural Values, In: Journal of International Marketing 1(33), doi:10.1177/1069031x241262728
  • Pratik Rai, Sasadhar Bera (2024): Machine learning-based empirical investigation of user’s perception of digitalisation in pandemic immunisation programs, In: Journal of Decision Systems, doi:10.1080/12460125.2024.2365492
  • David Goyeneche, Stephen Singaraju, Luis Arango (2023): Linked by age: a study on social media privacy concerns among younger and older adults, In: Industrial Management & Data Systems 2(124), doi:10.1108/imds-07-2023-0462
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