Filling in the Blanks: A Theory of Cognitive Categories and the Structure of Social Affiliation

Freeman, Linton C.

doi:10.2307/2786941

Cited by 235 publications

(124 citation statements)

References 27 publications

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“…The reliability of existing measures for relationships has been the subject of sharp debate over the last 30 years, starting with a series of landmark studies in which it was found that behavioral observations were surprisingly weakly related to reported interactions (8)(9)(10). There are multiple layers of cognitive filters that influence whether a subject reports a behavior (11). Existing research suggests that people are good at recalling long-term, but not short-term, social structures (12).…”

Section: Resultsmentioning

confidence: 99%

Inferring friendship network structure by using mobile phone data

Eagle

Pentland

Lazer

2009

Proc. Natl. Acad. Sci. U.S.A.

1,631

1,207

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Data collected from mobile phones have the potential to provide insight into the relational dynamics of individuals. This paper compares observational data from mobile phones with standard self-report survey data. We find that the information from these two data sources is overlapping but distinct. For example, selfreports of physical proximity deviate from mobile phone records depending on the recency and salience of the interactions. We also demonstrate that it is possible to accurately infer 95% of friendships based on the observational data alone, where friend dyads demonstrate distinctive temporal and spatial patterns in their physical proximity and calling patterns. These behavioral patterns, in turn, allow the prediction of individual-level outcomes such as job satisfaction.engineering-social systems ͉ relational inference ͉ social network analysis ͉ reality mining ͉ relational scripts T he field devoted to the study of the system of human interactions-social network analysis-has been constrained in accuracy, breadth, and depth because of its reliance on self-report data. Social network studies relying on self-report relational data typically involve both limited numbers of people and a limited number of time points (usually one). As a result, social network analysis has generally been limited to examining small, well-bounded populations, involving a small number of snapshots of interaction patterns (1). Although important work has been done over the last 30 years to analyze the relationship between self-reported and observed behavior, much of the social network literature is written as if self-report data are behavioral data.There is, however, a small but emerging thread of research examining social communication patterns based on directly observable data such as e-mail (2, 3) and call logs (4,5). Here, we demonstrate the power of collecting not only communication information but also location and proximity data from mobile phones over an extended period, and compare the resulting behavioral social network to self-reported relationships from the same group. We show that pairs of individuals that report themselves as friends demonstrate distinctive behavioral signatures as measured only by the mobile phone data. Further, these purely objective measures of behavior show powerful relationships with key outcomes of interest at the individual levelnotably, satisfaction.The Reality Mining study followed 94 subjects using mobile phones preinstalled with several pieces of software that recorded and sent the researcher data about call logs, Bluetooth devices in proximity of approximately five meters, cell tower IDs, application usage, and phone status (6, 7). Subjects were observed using these measurements over the course of nine months and included students and faculty from two programs within a major research institution. We also collected self-report relational data from each individual, where subjects were asked about their proximity to, and friendship with, others. Subjects were also asked about their satisf...

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Section: Resultsmentioning

confidence: 99%

Inferring friendship network structure by using mobile phone data

Eagle

Pentland

Lazer

2009

Proc. Natl. Acad. Sci. U.S.A.

1,631

1,207

View full text Add to dashboard Cite

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“…People seem not to be very good at seeing structural holes 'from the inside,' unless they already live in a hole-fi lled world. For example, in summarizing several studies (Freeman, 1992;Janicki and Larrick, 2005), he concluded, 'the summary conclusion from Freeman's and Janicik's experiments is that experience matters: people who live in a network that contains structural holes are more likely to recognize the holes in their next networks' (Burt, 2005: 77). …”

Section: Breaking Out Of Clustersmentioning

confidence: 99%

Small worlds, infinite possibilities? How social networks affect entrepreneurial team formation and search

Aldrich

Kim

2007

Strategic Entrepreneurship

286

178

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“…Relational schemas help people process -memorize, interpret and recall -information about otherwise overly intricate interpersonal structures (Baldwin, 1992;Janicik & Larrick, 2005;Ridgeway, 2006). Like all cognitive representations, relational schemas do not yield perfectly accurate pictures of reality, and research has documented various systematic biases stemming from schema activation (Freeman, 1992;Kilduff et al, 2008;. Despite these biases, relational schemas are indispensable "information compression heuristics" helping people to cognitively map the network of interpersonal relations surrounding them and, as such, they are necessary to interact competently with others (Brashears, 2013;Crockett, 1982b).…”

Section: Theory People Hold a Linear-ordering Schema To Process Leadementioning

confidence: 99%

“…To test it, we performed a "network learning experiment" analogous to the one developed by Janicik and Larrick (2005: 351-2 -Study 1), who in their turn followed a long and wellestablished tradition of experimental research on relational schemas (De Soto, 1960;Henley et al, 1969;Freeman, 1992). This experimental approach leverages the fact that, although people's schemas cannot not be directly observed, they can be inferred by observing how subjects' learning rates change in schema-consistent versus schema-inconsistent conditions.…”

Section: Studymentioning

confidence: 99%

Emergent Leadership Structures in Informal Groups: A Dynamic, Cognitively Informed Network Model

Carnabuci

Emery

Brinberg

2018

Organization Science

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This paper advances novel theory and evidence on the emergence of informal leadership networks in groups that feature no formally designated leaders or authority hierarchies. Integrating insights from relational schema and network theory, we develop and empirically test a 3-step process model. The model's first hypothesis is that people use a "linear-ordering schema" to process information about leadership relations. Taking this hypothesis as a premise, the second hypothesis argues that whenever an individual experiences a particular leadership attribution to be inconsistent with the linear-ordering schema, s/he will tend to reduce the ensuing cognitive inconsistency by modifying that leadership attribution. Finally, the third hypothesis builds on this inconsistency-reduction mechanism to derive implications about a set of network-structural features (asymmetry, a-cyclicity, transitivity, popularity, and inverse-popularity) that are predicted to endogenously emerge as a group's informal leadership network evolves. We find broad support for our proposed theoretical model using a multi-method, multi-study approach combining experimental and empirical data. Our study contributes to the organizational literature by illuminating a socio-cognitive dynamics underpinning the evolution of informal leadership structures in groups where formal authority plays a limited role.

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Filling in the Blanks: A Theory of Cognitive Categories and the Structure of Social Affiliation

Cited by 235 publications

References 27 publications

Inferring friendship network structure by using mobile phone data

Inferring friendship network structure by using mobile phone data

Small worlds, infinite possibilities? How social networks affect entrepreneurial team formation and search

Emergent Leadership Structures in Informal Groups: A Dynamic, Cognitively Informed Network Model

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