{"title":"规则网:使用关联规则和网络图映射文化偏好的结构","authors":"Neha Gondal","doi":"10.1016/j.poetic.2025.101996","DOIUrl":null,"url":null,"abstract":"<div><div>Sociologists have persuasively argued that cultural meaning can be interpreted by analyzing the systems of relations that measure the so-called ‘going together’ of cultural materials. Research investigating cultural tastes and preferences has used this approach to interpret consumption patterns as relational systems using a variety of techniques including multidimensional scaling, two-mode network analysis, and variable correlation networks. I contribute to this growing set of tools by describing and demonstrating the use of a datamining technique with scant history of use within sociology, called ‘association-rules.’ The key contribution of this technique is that it generates directed relationships between variables (e.g., preference for opera → preference for ballet), which has several advantages over existing techniques that conceptualize relationality in terms of mutual presence. I show how such ‘one-sided’ clustering (A goes with B, but B may not go together with A) can be represented and analyzed as network graphs, an approach I call ‘Rulenet.’ I discuss how the proposed technique can provide relatively novel insights into the organizations of tastes, less feasible via other techniques, and illustrate Rulenet on two well-known cultural participation survey datasets for the United States: (1) The Survey of Public Participation in the Arts (SPPA) from 2017 and (2) The General Social Survey Culture Module from 1993 (GSS).</div></div>","PeriodicalId":47900,"journal":{"name":"Poetics","volume":"110 ","pages":"Article 101996"},"PeriodicalIF":1.7000,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Rulenet: Mapping the structure of cultural preferences using association-rules and network graphs\",\"authors\":\"Neha Gondal\",\"doi\":\"10.1016/j.poetic.2025.101996\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Sociologists have persuasively argued that cultural meaning can be interpreted by analyzing the systems of relations that measure the so-called ‘going together’ of cultural materials. Research investigating cultural tastes and preferences has used this approach to interpret consumption patterns as relational systems using a variety of techniques including multidimensional scaling, two-mode network analysis, and variable correlation networks. I contribute to this growing set of tools by describing and demonstrating the use of a datamining technique with scant history of use within sociology, called ‘association-rules.’ The key contribution of this technique is that it generates directed relationships between variables (e.g., preference for opera → preference for ballet), which has several advantages over existing techniques that conceptualize relationality in terms of mutual presence. I show how such ‘one-sided’ clustering (A goes with B, but B may not go together with A) can be represented and analyzed as network graphs, an approach I call ‘Rulenet.’ I discuss how the proposed technique can provide relatively novel insights into the organizations of tastes, less feasible via other techniques, and illustrate Rulenet on two well-known cultural participation survey datasets for the United States: (1) The Survey of Public Participation in the Arts (SPPA) from 2017 and (2) The General Social Survey Culture Module from 1993 (GSS).</div></div>\",\"PeriodicalId\":47900,\"journal\":{\"name\":\"Poetics\",\"volume\":\"110 \",\"pages\":\"Article 101996\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2025-03-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Poetics\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0304422X25000269\",\"RegionNum\":2,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"0\",\"JCRName\":\"LITERATURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Poetics","FirstCategoryId":"90","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0304422X25000269","RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"LITERATURE","Score":null,"Total":0}
Rulenet: Mapping the structure of cultural preferences using association-rules and network graphs
Sociologists have persuasively argued that cultural meaning can be interpreted by analyzing the systems of relations that measure the so-called ‘going together’ of cultural materials. Research investigating cultural tastes and preferences has used this approach to interpret consumption patterns as relational systems using a variety of techniques including multidimensional scaling, two-mode network analysis, and variable correlation networks. I contribute to this growing set of tools by describing and demonstrating the use of a datamining technique with scant history of use within sociology, called ‘association-rules.’ The key contribution of this technique is that it generates directed relationships between variables (e.g., preference for opera → preference for ballet), which has several advantages over existing techniques that conceptualize relationality in terms of mutual presence. I show how such ‘one-sided’ clustering (A goes with B, but B may not go together with A) can be represented and analyzed as network graphs, an approach I call ‘Rulenet.’ I discuss how the proposed technique can provide relatively novel insights into the organizations of tastes, less feasible via other techniques, and illustrate Rulenet on two well-known cultural participation survey datasets for the United States: (1) The Survey of Public Participation in the Arts (SPPA) from 2017 and (2) The General Social Survey Culture Module from 1993 (GSS).
期刊介绍:
Poetics is an interdisciplinary journal of theoretical and empirical research on culture, the media and the arts. Particularly welcome are papers that make an original contribution to the major disciplines - sociology, psychology, media and communication studies, and economics - within which promising lines of research on culture, media and the arts have been developed.