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Sociological studies on transnational migration are often based on surveys or interviews, an expensive and time consuming approach. On the other hand, the pervasiveness of mobile phones and location aware social networks has introduced new ways to understand human mobility patterns at a national or global scale. In this work, we leverage geo located information obtained from Twitter as to understand transnational migration patterns between two border cities (San Diego, USA and Tijuana, Mexico). We obtained 10.9 million geo located tweets from December 2013 to January 2015. Our method infers human mobility by inspecting tweet submissions and users home locations. Our results depict a trans national community structure that exhibits the formation of a functional metropolitan area that physically transcends international borders. These results show the potential for re analysing sociology phenomena from a technology based empirical perspective.
DNS is a vital component for almost every networked application. Originally it was designed as an unencrypted protocol, making user security a concern. DNS-over-HTTPS (DoH) is the latest proposal to make name resolution more secure. In this paper we
Online government petitions represent a new data-rich mode of political participation. This work examines the thus far understudied dynamics of sharing petitions on social media in order to garner signatures and, ultimately, a government response. Us
The spreading COVID-19 misinformation over social media already draws the attention of many researchers. According to Google Scholar, about 26000 COVID-19 related misinformation studies have been published to date. Most of these studies focusing on 1
Topological aspects, like community structure, and temporal activity patterns, like burstiness, have been shown to severly influence the speed of spreading in temporal networks. We study the influence of the topology on the susceptible-infected (SI)
We advance binational link-tracing sampling design, an innovative data collection methodology for sampling from transnational social fields, i.e., transnational networks embedding migrants and non-migrants. This paper shows the practical challenges o