Modeling Individual-Level Infection Dynamics Using Social Network Information
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The ubiquity of social media in our daily life, the intense user participation, and the explosion of multimedia content have generated an extraordinary interest from computer and social scientists to investigate the traces left by users to understand human ...
The ubiquity of social media in our daily life, the intense user participation, and the explo- sion of multimedia content have generated an extraordinary interest from computer and social scientists to investigate the traces left by users to understand hum ...
Social network analysis is now widely used to investigate the dynamics of infectious disease spread. Vaccination dramatically disrupts disease transmission on a contact network, and indeed, high vaccination rates can potentially halt disease transmission a ...
Social media has been considered as a data source for tracking disease. However, most analyses are based on models that prioritize strong correlation with population-level disease rates over determining whether or not specific individual users are actually ...
The ability to identify people that share one's own interests is one of the most interesting promises of the Web 2.0 driving user-centric applications such as recommendation systems or collaborative marketplaces. To be truly useful, however, information ab ...
The emergence of social media has created new ways to publish scientific work, foster collaboration, and build professional connections in the research community. The rich data collected in social media platforms has provided new opportunities for assessin ...
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Institute of Electrical and Electronics Engineers2015
We study the problem of privacy-preserving computation of functions of data that belong to users in a social network under the assumption that users are willing to share their private data with trusted friends in the network. We demonstrate that such trust ...
