The Geography of Money and Politics: Population Density, Social Networks and Political Contributions

2015 ◽  
Author(s):  
Yu-Ru Lin ◽  
David Lazer ◽  
Ryan Kennedy
Keyword(s):  
Social Networks ◽  
Population Density ◽  
Political Contributions

scholarly journals The geography of money and politics: Population density, social networks, and political contributions

2017 ◽  
Vol 4 (4) ◽  
pp. 205316801774201
Author(s):  
Yu-Ru Lin ◽  
Ryan Kennedy ◽  
David Lazer
Keyword(s):  
Social Networks ◽  
Population Density ◽  
Social Networking ◽  
Political Contributions ◽  
Federal Election Commission ◽  
The Social ◽  
Populated Region ◽  
Geographical Space ◽  
Election Commission

We examine the social antecedents of contributing to campaigns, with a particular focus on the role of population density and social networking opportunities. Using 10 years of US campaign contribution data from the Federal Election Commission and a national survey of party leaders, we find that recruiting contributors is easier in a densely populated region, where the daily opportunity of individuals being exposed to the same information via their social networks is high. Furthermore, the effect of population density is heterogeneous with respect to mobility: if a region has substantial commuting outflow, the chance of being mobilized from the place of residence decreases, but the chance of mobilization in their place of work increases. This analysis also reveals differences between political parties. Democrats are more dependent on social networking in population dense areas. This difference in the importance of social networking opportunities present in geographical space helps explain macro-level patterns in party fundraising.

scholarly journals Statistical Model for Mobile User Positioning Based on Social Information

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1782
Author(s):  
Juan Luis Bejarano-Luque ◽  
Matías Toril ◽  
Mariano Fernández-Navarro ◽  
Luis Roberto Jiménez ◽  
Salvador Luna-Ramírez
Keyword(s):  
Social Networks ◽  
Population Density ◽  
Mobile Networks ◽  
Mobile User ◽  
Data Traffic ◽  
Huge Amount ◽  
User Context ◽  
Term Evolution ◽  
User Location

In spite of the vast set of measurements provided by current mobile networks, cellular operators have problems pinpointing problematic locations because the origin of such measurements (i.e., user location) is usually not registered. At the same time, social networks generate a huge amount of data that can be used to infer population density. In this work, a data-driven model is proposed to deduce the statistical distribution of connections, exploiting the knowledge of network layout and population density in the scenario. Due to the absence of GPS measurements, the proposed method combines data from radio connection traces stored in the network management system and geolocated posts from social networks. This information is enriched with user context information inferred from data traffic attributes. The method is tested with a large trace dataset from a live Long Term Evolution (LTE) network and a database of geotagged posts from social networks collected in real-time.

Multilayer Social Networks

2016 ◽  
Author(s):  
Mark E. Dickison ◽  
Matteo Magnani ◽  
Luca Rossi
Keyword(s):  
Social Networks ◽  
Multilayer Social Networks

Hostility and Perceptions of Support in Ambiguous Social Interactions

2006 ◽  
Vol 27 (2) ◽  
pp. 108-115 ◽  
Author(s):  
Ana-Maria Vranceanu ◽  
Linda C. Gallo ◽  
Laura M. Bogart
Keyword(s):  
Social Support ◽  
Social Networks ◽  
Information Processing ◽  
Social Interactions ◽  
Social Information Processing ◽  
Perceived Social Support ◽  
Social Information ◽  
Inverse Association ◽  
Processing Bias ◽  
Information Processing Bias

The present study investigated whether a social information processing bias contributes to the inverse association between trait hostility and perceived social support. A sample of 104 undergraduates (50 men) completed a measure of hostility and rated videotaped interactions in which a speaker disclosed a problem while a listener reacted ambiguously. Results showed that hostile persons rated listeners as less friendly and socially supportive across six conversations, although the nature of the hostility effect varied by sex, target rated, and manner in which support was assessed. Hostility and target interactively impacted ratings of support and affiliation only for men. At least in part, a social information processing bias could contribute to hostile persons' perceptions of their social networks.

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