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Location Sharing: Women Respond to Trust; Men Share to Connect with Others

EasyChair Preprint no. 1289

2 pagesDate: July 15, 2019


Location-enabled applications are providing tremendous insights for online communities, e-commerce and AI. Despite significant investments by companies such as Facebook, Google, Tindr, FourSquare, mobile applications and websites see only minor usage. Users in a community benefit from algorithms that create insights which improve a user’s experience based on location. Location-sharing interactions are qualitatively different than traditional social networking activities. Broadcasting location online or sharing with providers remains uncomfortable for many users. In addition, location-sharing interactions that combine online and offline exchanges come with risks to privacy and security—often dissuading sharing behaviors. We develop and test an interdisciplinary causal model for the determinants of location-sharing. While trust perceptions and critical mass in social channels were found to influence participation overall, trust is more important for women, and critical mass is more important for men. Both trust propensity and structural assurances influence interpersonal trust, but trust propensity has no apparent effect on men. These findings offer practical insights for UI/UX, augment marketing applications, support new trends AI/ML for social media, and can provide a theoretical foundation for future research.

Research Questions

1.How do trust beliefs in other network users—friends and strangers—influence a location-sharing technology’s use?
2.What are the antecedents of these trust beliefs?

Keyphrases: location sharing, motivations, online communities, social media, social networks, Trust

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Paul Russo and Jeancarlo Bonilla},
  title = {Location Sharing: Women Respond to Trust; Men Share to Connect with Others},
  howpublished = {EasyChair Preprint no. 1289},

  year = {EasyChair, 2019}}
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