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A Multilevel Study of Interpersonal Influence in Academic ‘Influence Networks’
Unformatted Document Text:  Influence Networks 22 correlation between Centrality 2 and indegree motivation to comply did not alter the findings that were based on aggregating all thirteen departments (r = .12, p = .22, N = 111). -- Figures 1 to 3 -- Although average indegree does not appear to be a structural variable that mediates the relationship between centrality and influence, Mizruchi and Potts found, through computer simulations, that the structure of the network plays a large role in determining how much influence central individuals possess (1998). In particular, the number of subgroups in the network mediates the influencing force of central individuals: power is weakened when there is interconnectivity among an odd number of these sub-grouped individuals, and it is strengthened when there is an even number of sub-groupings regardless of their interconnectivity. Systematic study that manipulates network configuration along these dimensions (number of groups and their relative interconnectivity) can add to the conclusions drawn from Mizruchi and Potts’ work to advance knowledge about what structural properties bear on the centrality-influence link. It is relevant to emphasize that the influence networks used in this study were constructed with incomplete data, where response rates for each network ranged from 31 to 65 percent. Though missing data are not expected to seriously impact Centrality 1 (Costenbader & Valente, in press), Centrality 2 is sensitive to missing data because it is based on average indegree scores within the network, and the missing data could have influenced the degree to which each centrality score was adjusted. A more conclusive test of this structural mediator of the centrality- influence link would be to conduct a similar study with complete network data so that Centrality 1 and Centrality 2 can be directly compared in terms of the predictive value that each network position possesses.

Authors: Wolski, Stacy.
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Influence Networks 22
correlation between Centrality
2
and indegree motivation to comply did not alter the findings that
were based on aggregating all thirteen departments (r = .12, p = .22, N = 111).
-- Figures 1 to 3 --
Although average indegree does not appear to be a structural variable that mediates the
relationship between centrality and influence, Mizruchi and Potts found, through computer
simulations, that the structure of the network plays a large role in determining how much
influence central individuals possess (1998). In particular, the number of subgroups in the
network mediates the influencing force of central individuals: power is weakened when there is
interconnectivity among an odd number of these sub-grouped individuals, and it is strengthened
when there is an even number of sub-groupings regardless of their interconnectivity. Systematic
study that manipulates network configuration along these dimensions (number of groups and
their relative interconnectivity) can add to the conclusions drawn from Mizruchi and Potts’ work
to advance knowledge about what structural properties bear on the centrality-influence link.
It is relevant to emphasize that the influence networks used in this study were constructed
with incomplete data, where response rates for each network ranged from 31 to 65 percent.
Though missing data are not expected to seriously impact Centrality
1
(Costenbader & Valente, in
press), Centrality
2
is sensitive to missing data because it is based on average indegree scores
within the network, and the missing data could have influenced the degree to which each
centrality score was adjusted. A more conclusive test of this structural mediator of the centrality-
influence link would be to conduct a similar study with complete network data so that Centrality
1
and Centrality
2
can be directly compared in terms of the predictive value that each network
position possesses.


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