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Online Social Sport Networks

Online Social Sport Networks. Bas Stottelaar , Jeroen Sender & Lorena Montoya. Stottelaar , B. and Senden, J. and Montoya Morales, A.L. (2014) Online Social Sports Networks as Crime Facilitators. Crime Science, 3. 8:1-8:14. ISSN 2193-7680. Emerging technologies.

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Online Social Sport Networks

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  1. Online Social Sport Networks Bas Stottelaar, Jeroen Sender & Lorena Montoya Stottelaar, B. and Senden, J. and Montoya Morales, A.L. (2014) Online Social Sports Networks as Crime Facilitators. Crime Science, 3. 8:1-8:14. ISSN 2193-7680

  2. Emerging technologies Specialized online social networks MapMyRun Nike + Running Zombies, Run! Endomondo • Why is this interesting/relevant? • Privacy considerations of geo-location and tracking are discussed in relation to enterprises. • Studies usually operationalize ‘leisure’ as pubbing • Time available for leisure is on the rise! Runkeeper Cyber-crime Science

  3. Whybother? • Implications of thisfor: • Safety of the house (burglary) • Disclosure of personal information (e.g. violent crime, fraud). Cyber-crime Science

  4. Research questions • Accuracy of address based on OSSN routes; NL implication? • More OSSN disclosure than via other online sources? • Age and gender differences? Cyber-crime Science

  5. Other online sources • Facebook • Yellow pages • LinkedIn • Twitter • etc. Cyber-crime Science

  6. Procedure • Sample of 513 randomly selected Runkeepers • Tip 1: min. sample size • Retrieval of run’s star-end xy coordinates & algorithm predicting home address • Algorithm validation using volunteer runners • Search for home address, age and gender on Runkeeper website and other online sources • Statistical analysis Cyber-crime Science

  7. Tip. 2 : Intuitivecoding • Multinomialdependent variable: Disclosure: None = 0 Runkeeper = 1 Other = 2 Both = 3 • Independent variables Via Runkeeper (yes = 1, no = 0) Via other sources (yes =1, no = 0) Via both (yes = 1, no = 0) Gender (female = 1, male = 0) Age (categories with 5 year increments) Cyber-crime Science

  8. The not-so-cool findings… • Tip 3: findinterpretationexamples ** p<0.01 Cyber-crime Science

  9. Tip 4: Show beyond the results • Advancing theory: • The more specialized the network, the more disclosure of private information? • People friends strangers more in more specialized social networks? • Practice: • In NL high density low-rise residential context, within 8 possible houses. • Anticipate problems Cyber-crime Science

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