2012 KAIST-Southampton Workshop Group3

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2012 KAIST-Southampton Workshop Group3

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2012 KAIST-Southampton Workshop Group3

  1. 1. + Group 3 Cultural perspectives on Twitter privacy & security in Korea & the UK
  2. 2. Research questions Potential research questions that this work will enable…  Are people using Twitter as a social media for broadcasting or for social networking? How does this differ between Korea and U.K.  At what rate are users changing from public to private, and how is this different between Korea and U.K.? Also, in which direction is it changing?  Can we infer what drives users to switch their status from public to private based on Twitter data?  a string of bad comments that have influenced someone to go private – could be discovered with network analysis (also look at the number followers for example)  sentiment analysis to determine the moods of the tweeter – does your mood effect your decision to go private This week…  can we build a proof of concept that shows these questions can be answered
  3. 3. Method - This week goals Literature check Gather tweet samples Korea & UK Measure proportion of public & private users Identify users who have recently switched privacy status
  4. 4. Possible additional work: Analyse tweets around the point at which privacy status switches to identify possible motivating factors  Possible approaches: natural language processing, sentiment analysis & network analysis Possibly compare with other privacy-related factors such as publishing location, linking to homepage/facebook, using HTTPS, use of avatars vs photos
  5. 5. Results Mock-up4540353025 Korea (% private)20 UK (% private)15 Rate of change of users from10 public to private Twitter setting 5 0 6 0 2 4 6 8 10 12 4 Proportion of users with private 2 vs. public Twitter setting 0 Korea Change 0 2 4 6 8 10 12 UK Change -2 -4 -6 -8
  6. 6. Potential issues Identifying active but private accounts? Issues driving people to change privacy settings that are not reflected in publically available tweets. Privacy aware users might not declare nationality, thus skewing results. Other issues with identifying nationality/location Ethics
  7. 7. + Results
  8. 8. Research questions “Investigating cultural differences based on privacy and security attitudes of UK and Korean people online” This week…  Attempted to build a proof of concept that shows these questions can be answered
  9. 9. Public vS Private Twitter Accounts 50000000 45000000 40000000 Number of Twitter 35000000 Accounts 30000000 Number of 25000000 Protected Twitter 20000000 Accounts 15000000 10000000 50000000 0 2009 2010 2011 2012 Total Data taken from WhisThis.com (2012)
  10. 10. Visualisation I – User Profile Data Percentage of protected and location-enabled accounts 40.00 35.00 30.00 25.00 South Korea 20.00 15.00 UK 10.00 5.00 0.00 location-enabled protected
  11. 11. Visualisation II – Public to PrivateAccounts and vice versaPublic to private (S. Korea) Private to public (S. Korea) 1% 13% private private public public 87% 99%
  12. 12. Visualisation III Evolution of location-enabled tweets (UK) 25000 20000 15000 10000 location-enabled total_tweet 5000 0
  13. 13. Visualisation IV – Real-time Geotagged Tweets http://users.ecs.soton.ac.uk/rwf1v07/privacywatch/
  14. 14. Future Work Continue on Twitter data extraction to complete the graphs Investigate further research questions  Twitter: Social media or Social Network?  Why people change their profiles from public to private?  What are the cultural differences between Koreans and English with regards to privacy?
  15. 15. + Thank you!

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