Political and Occupational Cleavages in a Hanoverian Village, Germany: A Sociometric Study

Loomis, Charles

doi:10.2307/2785496

Cited by 97 publications

(29 citation statements)

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“…This homophily-based model is motivated by observations and theories of social networks (Blau, 1977;McPherson et al, 2001), where homophily is ubiquitous. Homophily was one of the first characteristics noted by early social network researchers (Almack, 1922;Bott, 1928;Richardson, 1940;Loomis, 1946;Lazarsfeld and Merton, 1954), and holds for a wide variety of different relationships (McPherson et al, 2001). It seems reasonable to conjecture that homophily may also be present in other sorts of networks, especially networks of artifacts created by people.…”

Section: Weighted-vote Relational Neighbor Classifier (Wvrn)mentioning

confidence: 99%

Classificaiton in Networked Data: A Toolkit and a Univariate Case Study

Macskassy¹,

Provost²

2005

200

486

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This paper presents NetKit, a modular toolkit for classification in networked data, and a case-study of its application to a collection of networked data sets used in prior machine learning research. Networked data are relational data where entities are interconnected, and this paper considers the common case where entities whose labels are to be estimated are linked to entities for which the label is known. NetKit is based on a three-component framework, comprising a local classifier, a relational classifier, and a collective inference procedure. Various existing relational learning algorithms can be instantiated with appropriate choices for these three components and new relational learning algorithms can be composed by new combinations of components. The case study demonstrates how the toolkit facilitates comparison of different learning methods (which so far has been lacking in machine learning research). It also shows how the modular framework allows analysis of subcomponents, to assess which, whether, and when particular components contribute to superior performance. The case study focuses on the simple but important special case of univariate network classification, for which the only information available is the structure of class linkage in the network (i.e., only links and some class labels are available). To our knowledge, no work previously has evaluated systematically the power of class-linkage alone for classification in machine learning benchmark data sets. The results demonstrate clearly that simple network-classification models perform remarkably well-well enough that they should be used regularly as baseline classifiers for studies of relational learning for networked data. The results also show that there are a small number of component combinations that excel, and that different components are preferable in different situations, for example when few versus many labels are known.

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Section: Weighted-vote Relational Neighbor Classifier (Wvrn)mentioning

confidence: 99%

Classificaiton in Networked Data: A Toolkit and a Univariate Case Study

Macskassy¹,

Provost²

2005

200

486

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“…This favours the resolution of disruptive disagreements, the achievement of consensus, and it promotes a positive view of the group as a social unit [17]. Loomis’ classic study [18] reflects that homophily relates to psychological characteristics such as intelligence, attitudes, and aspirations. People who have homophilic relationships share common characteristics such as beliefs, values, education, etc.…”

Section: Introductionmentioning

confidence: 99%

“…which makes communication and the creation of a relationship much easier. On the other hand, homophily also allows a person to know what attributes are seen as important within a group [18]. Similarities encourage people who are a part of a group in which friendship is formed, favouring the acceptance of pairs [19].…”

Section: Introductionmentioning

confidence: 99%

Social Network Analysis and Resilience in University Students: An Approach from Cohesiveness

Liébana‐Presa

Díaz

Reguera-García

et al. 2018

IJERPH

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The Social Network Analysis offers a view of social phenomena based on interactions. The aim of this study is to compare social reality through the cohesion variable and analyse its relationship with the resilience of university students. This information is useful to work with the students academically and to optimise the properties of the network that have an influence in academic performance. This is a descriptive transversal study with 90 students from the first and third year of the Nursing Degree. Cohesion variables from the support and friendship networks and the level of resilience were gathered. The UCINET programme was used for network analysis and the SPSS programme for statistical analysis. The students’ friendship and support networks show high intra-classroom cohesion although there are no differences between the support networks and friendship or minimal contact networks in both of the courses used for the study. The network cohesion indicators show less cohesion in the third year. No correlations were found between cohesion and resilience. Resilience does not appear to be an attribute related to cohesion or vice versa.

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“…It refers to the frequent finding (Bott, 1928;Loomis, 1946) that agents in a network have a higher-than-random chance of being linked to someone similar to themselves (for a review see McPherson, Smith-Lovin and Cook, 2001). Homophily may be the result of either selection -we make friends with people like us -or adaptation, that is, once we are acquainted to someone, we tend to adapt his or her behavior, manners or opinions (see Baccara and Yariv, 2013, for a theoretical model).…”

Section: Homophily In Trustworthinessmentioning

confidence: 99%

You Are Who Your Friends Are: An Experiment on Trust and Homophily in Friendship Networks

Winter

Kataria

2013

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractWe study the existence of homophily (i.e. the tendency for people to make friends with people who are similar to themselves) with respect to trustworthiness. We ask whether two friends show similarly trustworthy behavior towards strangers, and whether this is anticipated by outsiders. We develop a simple model of bayesian learning in trust games and test the derived hypotheses in a controlled laboratory environment. In the experiment, two trustees sequentially play a trust game with the same trustor, where the trustees depending on treatmen are either friends or strangers to each other. We affirm the existence of homophily with respect to trustworthiness. Trustors' beliefs about the trustees' trustfulness are not affected by the knowledge about the (non-)existent friendship between the trustees. Behaviorally, however, they indirectly reciprocate the (un-)trustworthy behavior of one trustee towards his/her friends in later interactions.Keywords: social networks homophily trust friendship indirect tit-for-tat JEL Classification C92 · D83 · J24 · J40 *

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Political and Occupational Cleavages in a Hanoverian Village, Germany: A Sociometric Study

Cited by 97 publications

References 0 publications

Classificaiton in Networked Data: A Toolkit and a Univariate Case Study

Classificaiton in Networked Data: A Toolkit and a Univariate Case Study

Social Network Analysis and Resilience in University Students: An Approach from Cohesiveness

You Are Who Your Friends Are: An Experiment on Trust and Homophily in Friendship Networks

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