Privacy and Web 3.0: Implementing Trust and Learning From Social Networks

  •  George Bouchagiar    


After having shifted from Web 1.0 to Web 2.0, scientists welcome the advent of Web 3.0, an environment where meaning is added to data. While in the Semantic Web people are no longer users, but part of the emerging applications, producers, subjects and beneficiaries of the Big Data, however, opaque processing of personal data poses tremendous risks and dangers for individuals. Given the new era of Big Data this paper studies firms’ purposes and practices to detect some emerging privacy risks. Moreover, theories that deal with social networks are examined to conclude that, even if people state that they value their privacy, however, they often disclose a huge volume of personal information. Taking into account that today’s European concept of privacy is conceptualized in negative terms this paper also proposes the implementation of trust and loyalty into the privacy concept through flexible fiduciary laws. Furthermore, data portability is discussed to detect its potential as a strategic feature, a key tool that will enhance trust. Finally, further scenarios and proposals are submitted, in our attempt to answer the question whether the European concept of privacy could be re-shaped for the benefit of individuals.

This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1918-7173
  • ISSN(Online): 1918-7181
  • Started: 2009
  • Frequency: quarterly

Journal Metrics

  • Google-based Impact Factor (2021): 0.85
  • h-index (December 2021): 35
  • i10-index (December 2021): 262
  • h5-index (December 2021): 18  
  • h5-median(December 2021): 24

( The data was calculated based on Google Scholar Citations. Click Here to Learn More. )