Structural and Cognitive Bottlenecks to Information Access in Social Networks
Jeon-Hyung Kang, Kristina Lerman

TL;DR
This study investigates how structural and cognitive factors in online social networks like Digg influence users' access to novel information, revealing bottlenecks that limit information diversity despite network connections.
Contribution
It extends traditional social network theories to online platforms, analyzing how network structure and activity affect information access and identifying specific bottlenecks in digital environments.
Findings
Linking to active users improves information access.
Structural diversity constraints reduce information novelty.
Users see only a small fraction of available information after recommendations.
Abstract
Information in networks is non-uniformly distributed, enabling individuals in certain network positions to get preferential access to information. Social scientists have developed influential theories about the role of network structure in information access. These theories were validated through numerous studies, which examined how individuals leverage their social networks for competitive advantage, such as a new job or higher compensation. It is not clear how these theories generalize to online networks, which differ from real-world social networks in important respects, including asymmetry of social links. We address this problem by analyzing how users of the social news aggregator Digg adopt stories recommended by friends, i.e., users they follow. We measure the impact different factors, such as network position and activity rate; have on access to novel information, which in…
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Taxonomy
TopicsComplex Network Analysis Techniques · Opinion Dynamics and Social Influence · Social Media and Politics
