97 research outputs found
Contrasting Multiple Social Network Autocorrelations for Binary Outcomes, With Applications To Technology Adoption
The rise of socially targeted marketing suggests that decisions made by
consumers can be predicted not only from their personal tastes and
characteristics, but also from the decisions of people who are close to them in
their networks. One obstacle to consider is that there may be several different
measures for "closeness" that are appropriate, either through different types
of friendships, or different functions of distance on one kind of friendship,
where only a subset of these networks may actually be relevant. Another is that
these decisions are often binary and more difficult to model with conventional
approaches, both conceptually and computationally. To address these issues, we
present a hierarchical model for individual binary outcomes that uses and
extends the machinery of the auto-probit method for binary data. We demonstrate
the behavior of the parameters estimated by the multiple network-regime
auto-probit model (m-NAP) under various sensitivity conditions, such as the
impact of the prior distribution and the nature of the structure of the
network, and demonstrate on several examples of correlated binary data in
networks of interest to Information Systems, including the adoption of Caller
Ring-Back Tones, whose use is governed by direct connection but explained by
additional network topologies
Balance Correlations, Agentic Zeros, and Networks: The Structure of 192 Years of War and Peace
Original balance theory (Heider 1944) predicts human relations based on
perceptions and attitudes between a pair of individuals (P - O) towards an
inanimate object X. Social network extensions of his theory have replaced this
X with a third individual. This has led to a plethora of adaptations that have
often been inconsistent with Heider and with each other. We present a general
model and formal notation for these social network extensions that permit
social scientists to be more explicit about their balance theoretic statements.
Specifically, we formulate statements as a comparison of two conditional
probabilities of a tie, where the conditionals are defined by the 2-path
relation Ego - X - Alter. Given the importance Heider assigns to the role of
negative associations, we further identify negative ties as separate from
non-ties (neutral or zero-valued ties) and consider a signed graph to be a
restricted multigraph composed of three mutually exclusive and exhaustive
relations: positive ties, negative ties, and zero-ties. We stress that
neutrality is the result of a triadic process. Combining these two features
into our theoretical frame results in 27 identifiable configurations. Drawing
on the work on Transitivity Correlation models, we propose a set of simple
descriptive statistics to measure the extent to which evidence for any
stipulated balance configuration is present in a network. Finally, we
demonstrate how to apply this approach to assess network-level balance in a
large data set consisting of friendly vs hostile relations between countries
from 1816 to 2007. We find strong evidence particularly for one of the four
classic Heiderian balance theory predictions, and virtually no evidence in
support of the imbalance predictions. However, we do find stable and surprising
evidence that `neutral' ties are important in balancing the relations among
nations.Comment: 31 pages, presented at Networks 2021, Bloomington, USA, Sunbelt 2022,
Cairns, Sunbelt 2023, Portland, Sunbelt 2023, Portland, USA, ION IX,
Lexington, USA, and EUSN 2023 Ljubljana, Sloveni
Generalized Blockmodeling with Pajek
Abstract One goal of blockmodeling is to reduce a large, potentially incoherent network to a smaller comprehensible structure that can be interpreted more readily. Batagelj, Doreian, and Ferligoj developed a generalized approach to blockmodeling and methods where a set of observed relations are fitted to a pre-specified blockmodel. In the paper this generalized blockmodeling approach as implemented in program Pajek is described. An overview of the blockmodeling procedures in Pajek is given and is illustrated by some examples
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