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 2193-7680Online Social Sports Networks as Crime Facilitators.

2. Emerging technologies Cyber-crime Science 2 Specialized online social networks MapMyRun Nike + Running Zombies, Run! Runkeeper 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!

3. Why bother? Implications of this for: »Safety of the house (burglary) »Disclosure of personal information (e.g. violent crime, fraud). Cyber-crime Science 3

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

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

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 6

7. Tip. 2 : Intuitive coding Multinomial dependent 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 7

8. The not-so-cool findings… Tip 3: find interpretation examples Cyber-crime Science 8 Variables RRR Relative risk ratio Runkeeper Age1.02 Female0.46** cons1.18 Other online sources Age1.28 Female0.51 cons0.24 Both Age1.46** Female0.55 cons0.20 ** p<0.01

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 9