國立虎尾科技大學 |

Statistical Models for Cognitive Social Structures.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Statistical Models for Cognitive Social Structures./
作者:	Shao, Kanghong.
面頁冊數:	1 online resource (47 pages)
附註:	Source: Masters Abstracts International, Volume: 57-06.
Contained By:	Masters Abstracts International57-06(E).
標題:	Statistics. -
電子資源:	click for full text (PQDT)
ISBN:	9780438081635

Statistical Models for Cognitive Social Structures.
Shao, Kanghong.

Statistical Models for Cognitive Social Structures. - 1 online resource (47 pages)

Source: Masters Abstracts International, Volume: 57-06.

Thesis (M.S.)--University of California, Los Angeles, 2018.

Includes bibliographical references

Cognitive social structures (CSS) is an area in social network research that has enduring importance but lacks flexible models. In this paper we consider statistical models for CSS systems where we observe a three-dimensional binary array of relational ties characterized by the "sender" of the relation, the "receiver" of the relation, and the "perceiver" of the relation from the "sender" to the "receiver". Such systems have been represented as networks by Krackhardt. Durante, Dunson and Vogelstein proposed a flexible Bayesian nonparametric approach to model the population distribution of network valued data, in which the joint distribution of the edges probabilities is defined through a mixture model that reduces dimensionality and incorporates information within each mixture component based on latent space models. Inspired by this work, we modify the model to characterize cognitive social structures by adding a parameter for cognitive error. As a case study, we apply our model to Krackhardt's network data of 21 managers in a high-tech machine manufacturing firm. The results show distinct effects of cognitive error and illustrate that our model is capable of characterizing cognitive social structures. The results also motivate future improvement on transitivity and triangle relations.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780438081635Subjects--Topical Terms:

556824
Statistics.
Index Terms--Genre/Form:

554714
Electronic books.

Statistical Models for Cognitive Social Structures.
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500 $a Source: Masters Abstracts International, Volume: 57-06.
500 $a Adviser: Mark Stephen Handcock.
502 $a Thesis (M.S.)--University of California, Los Angeles, 2018.
504 $a Includes bibliographical references
520 $a Cognitive social structures (CSS) is an area in social network research that has enduring importance but lacks flexible models. In this paper we consider statistical models for CSS systems where we observe a three-dimensional binary array of relational ties characterized by the "sender" of the relation, the "receiver" of the relation, and the "perceiver" of the relation from the "sender" to the "receiver". Such systems have been represented as networks by Krackhardt. Durante, Dunson and Vogelstein proposed a flexible Bayesian nonparametric approach to model the population distribution of network valued data, in which the joint distribution of the edges probabilities is defined through a mixture model that reduces dimensionality and incorporates information within each mixture component based on latent space models. Inspired by this work, we modify the model to characterize cognitive social structures by adding a parameter for cognitive error. As a case study, we apply our model to Krackhardt's network data of 21 managers in a high-tech machine manufacturing firm. The results show distinct effects of cognitive error and illustrate that our model is capable of characterizing cognitive social structures. The results also motivate future improvement on transitivity and triangle relations.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
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650 4 $a Social structure. $3 555182
655 7 $a Electronic books. $2 local $3 554714
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