Informant accuracy in social network data IV: a comparison of clique-level structure in behavioral and cognitive network data

Bernard, H. Russell; Killworth, Peter D.; Sailer, Lee

doi:10.1016/0378-8733(79)90014-5

Cited by 312 publications

(121 citation statements)

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“…When self-reports of recalled interactions have been compared to independent observations, however, the reliability of subjects' answers has been shockingly poor [Killworth and Bernard 1976;Killworth 1977, 1979;Bernard et al 1980Bernard et al , 1982. An early study came to the dire conclusion that "people do not know, with any accuracy, those with whom they communicate" [Bernard and Killworth 1977].…”

Section: Introductionmentioning

confidence: 99%

Inferring colocation and conversation networks from privacy-sensitive audio with implications for computational social science

Wyatt

Choudhury

Bilmes

et al. 2011

ACM Trans. Intell. Syst. Technol.

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New technologies have made it possible to collect information about social networks as they are acted and observed in the wild, instead of as they are reported in retrospective surveys. These technologies offer opportunities to address many new research questions: How can meaningful information about social interaction be extracted from automatically recorded raw data on human behavior? What can we learn about social networks from such fine-grained behavioral data? And how can all of this be done while protecting privacy? With the goal of addressing these questions, this article presents new methods for inferring colocation and conversation networks from privacysensitive audio. These methods are applied in a study of face-to-face interactions among 24 students in a graduate school cohort during an academic year. The resulting analysis shows that networks derived from colocation and conversation inferences are quite different. This distinction can inform future research in computational social science, especially work that only measures colocation or employs colocation data as a proxy for conversation networks. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies show this notice on the first page or initial screen of a display along with the full citation. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, to redistribute to lists, or to use any component of this work in other works requires prior specific permission and/or a fee. Permissions may be requested from Publications Dept., ACM, Inc., 2 Penn Plaza, Suite 701, New York, NY 10121-0701 USA, fax +1 (212) Wyatt, D., Choudhury, T., Bilmes, J., and Kitts, J. A. 2011. Inferring colocation and conversation networks from privacy-sensitive audio with implications for computational social science. ACM

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Section: Introductionmentioning

confidence: 99%

Inferring colocation and conversation networks from privacy-sensitive audio with implications for computational social science

Wyatt

Choudhury

Bilmes

et al. 2011

ACM Trans. Intell. Syst. Technol.

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“…The experiment also showed that the similarity structure of categories used in memory-based judgments is closer to those of the linguistic categories involved in expressing recovered memory and uncorrelated with those used in immediate judgments of these events. No wonder, then, that the studies of Bernard, Killworth, and Sailer (Bernard and Killworth 1977;Bernard et al 1980Bernard et al , 1982 and with Kronenfeld in Bernard et al 1984) showed that there is roughly only 50 percent agreement between the network links that people form and their mental recall of these links. Freeman et al (1987) showed that the "best" informants on behaviors in groups, according to consensus, "can be used to reveal long-range stable patterns of events," while average non-consensual judgments of the worst informants can be more useful "to reveal the details of a particular event of special interest" (the accident bystander phenomenon, for averaging perceptions of completely independent observers).…”

Section: Deeper Problems: Mind Logics and Worldmentioning

confidence: 99%

Social Networks, Cognition, and Culture

White¹

2011

A Companion to Cognitive Anthropology

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NETWORKSNetwork studies are an important adjunct to further development of cognitive anthropology and theory. When reliable means of identifying relational properties of behavior, cognition, and cultural structures or systems are available they help overcome limitations of other types of descriptive studies, descriptive statistics, or ad hoc inferences about how mind, culture, and social behavior interact. RolesRoles form into key network and institutional structures which can be understood in relation to social processes. Network ethnography can also operate in this way to further understanding (White and Johansen 2006:ch. 1). Network studies enhance our understandings of cause and effects of emergent roles and their dynamical patterns of shifting stability, including hierarchy. Finding hierarchy and its network embeddings, for example, often depends on global as well as local information on how local patterns fit within global ones. Both the understanding of global network structure and analysis of micro-macro linkages are additional advantages. If we wanted to find the leaders in a large urban community (see Freeman et al. 1960), for example, we could start from a sample of potential leaders, ask them who the leaders are, and iteratively construct a snowball sample of higher order leaders until finally a leader sub-network or evidence of a single leader emerges. Cohesive groupsCohesive groups have patterned interactions that are self-reinforcing and self-stabilizing in certain spatio-temporal frames. Study of these interactions can also account for individual choices, the emergence of cohesive units as socially and cognitively recognizable

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“…Several studies compared data gathered through objective records such as observation with sociometric questioning (Bernard & Killworth, 1977;Bernard, Killworth, Kronenfeld, & Sailer, 1984;Bernard, Killworth, & Sailer, 1980;Killworth & Bernard, 1976. They concluded that people cannot report with any accuracy the contacts they have had within a specific time frame.…”

Section: Sociometric Questioning Versus Observationmentioning

confidence: 99%

Auditing Information Structures in Organizations: A Review of Data Collection Techniques for Network Analysis

Zwijze‐Koning

Jong

2005

Organizational Research Methods

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Odiorne (1954) was the first researcher to use this term in the academic literature. He developed and used an audit to measure the accuracy and completeness of information transmitted between a company's management and its engineering staff. What is now considered an obvious audit result was a remarkable finding back then: The engineers felt surprisingly uninformed. Findings like these stress the importance of evaluating the quality of internal communication on a regular basis.

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Informant accuracy in social network data IV: a comparison of clique-level structure in behavioral and cognitive network data

Cited by 312 publications

References 10 publications

Inferring colocation and conversation networks from privacy-sensitive audio with implications for computational social science

Inferring colocation and conversation networks from privacy-sensitive audio with implications for computational social science

Social Networks, Cognition, and Culture

Auditing Information Structures in Organizations: A Review of Data Collection Techniques for Network Analysis

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