Social media can offer strategic communicators cost-effective opportunities to reach
millions of individuals. However, in practice it can be difficult to be heard in these
crowded digital spaces. This study takes a strategic network perspective and draws
from recent research in network science to propose the network contingency model of
public attention. This model argues that in the networked social-mediated environment,
an organization’s ability to attract public attention on social media is contingent on its
ability to fit its network position with the network structure of the communication
context. To test the model, we combine data mining, social network analysis, and
machine-learning techniques to analyze a large-scale Twitter discussion network. The
results of our analysis of Twitter discussion around the refugee crisis in 2016 suggest
that in high core-periphery network contexts, “star” positions were most influential
whereas in low core-periphery network contexts, a “community” strategy is crucial to
attracting public attention.
Saffer, Adam J.
Standing out in a networked communication context: Toward a network contingency model of public attention.
new media & society.
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