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Connectivity and community structure of online and register-based social networks
Connectivity and community structure of online and register-based social networks
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Connectivity and community structure of online and register-based social networks
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Connectivity and community structure of online and register-based social networks
Connectivity and community structure of online and register-based social networks

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Connectivity and community structure of online and register-based social networks
Connectivity and community structure of online and register-based social networks
Journal Article

Connectivity and community structure of online and register-based social networks

2025
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Overview
The dominance of online social media data as a source for large-scale social network studies has recently been challenged by networks constructed from state-curated register data. In this paper focused on the cross-comparison of the network structures, we investigate the similarities and differences of the Dutch online social network (OSN) Hyves and a register-based social network (RSN) of the Netherlands. First and foremost, we find that node metrics and the connectivity of the two population-scale networks are similar, with more long-distance ties captured by the OSN, and with the OSN ties proving to be predictive of RSN ties. These results hold when correcting for population size and geographical distance, notwithstanding that these two factors appear to be the main drivers of connectivity. Second, we show using multiple algorithms that the community structure of the two networks is similar and that neither follows strict administrative geographical delineations (e.g., provinces). Instead, communities appear to either center around large metropolitan areas or, outside of the country’s most urbanized area, comprise large blocks of interdependent municipalities. Beyond population and distance-related patterns, communities also highlight the persistence of deeply rooted sociocultural communities such as the Dutch Bible belt. The findings presented in this work aid in interpreting results from future studies in which register-based social networks are used to obtain insights into the social network structure of an entire population.