{"title":"关系事件模型能揭示什么?对托马斯-格伦德《谴责的动力》的评论:丑闻的局限性","authors":"","doi":"10.1140/epjds/s13688-023-00432-3","DOIUrl":null,"url":null,"abstract":"<h3>Abstract</h3> <p>This article provides a commentary on Thomas Grund’s International Conference on Computational Social Science 2021 keynote “Dynamics of Denunciation: The Limits of a Scandal”. The keynote presents results from research investigating the relational dynamics underpinning the denunciations provided in testimonies relating to a Canadian political scandal. Grund uses relational event models to test hypotheses about the social mechanisms driving the denunciations. Although denunciation should depend only on who is guilty and not on who has said what up to that point, Grund’s study finds evidence in support of a number of relational mechanisms influencing the denunciation process. Grund argues that the apparent influence of past denunciations on testimonies reveals the limits of the inquiry process itself and what it can reveal about a scandal. This article reviews Grund’s talk and puts the work in a broader context of using approaches rooted in event history modelling and social network theory to illuminate the processes defining social interaction data. It highlights ways in which the keynote can inform the development of computational social science approaches to analysing such data, and argues that the value of such an analysis has implications for scholarship beyond the social sciences.</p>","PeriodicalId":11887,"journal":{"name":"EPJ Data Science","volume":"86 1","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"What relational event models can reveal: Commentary on Thomas Grund’s “Dynamics of Denunciation: The Limits of a Scandal”\",\"authors\":\"\",\"doi\":\"10.1140/epjds/s13688-023-00432-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<h3>Abstract</h3> <p>This article provides a commentary on Thomas Grund’s International Conference on Computational Social Science 2021 keynote “Dynamics of Denunciation: The Limits of a Scandal”. The keynote presents results from research investigating the relational dynamics underpinning the denunciations provided in testimonies relating to a Canadian political scandal. Grund uses relational event models to test hypotheses about the social mechanisms driving the denunciations. Although denunciation should depend only on who is guilty and not on who has said what up to that point, Grund’s study finds evidence in support of a number of relational mechanisms influencing the denunciation process. Grund argues that the apparent influence of past denunciations on testimonies reveals the limits of the inquiry process itself and what it can reveal about a scandal. This article reviews Grund’s talk and puts the work in a broader context of using approaches rooted in event history modelling and social network theory to illuminate the processes defining social interaction data. It highlights ways in which the keynote can inform the development of computational social science approaches to analysing such data, and argues that the value of such an analysis has implications for scholarship beyond the social sciences.</p>\",\"PeriodicalId\":11887,\"journal\":{\"name\":\"EPJ Data Science\",\"volume\":\"86 1\",\"pages\":\"\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-01-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"EPJ Data Science\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1140/epjds/s13688-023-00432-3\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"EPJ Data Science","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1140/epjds/s13688-023-00432-3","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
What relational event models can reveal: Commentary on Thomas Grund’s “Dynamics of Denunciation: The Limits of a Scandal”
Abstract
This article provides a commentary on Thomas Grund’s International Conference on Computational Social Science 2021 keynote “Dynamics of Denunciation: The Limits of a Scandal”. The keynote presents results from research investigating the relational dynamics underpinning the denunciations provided in testimonies relating to a Canadian political scandal. Grund uses relational event models to test hypotheses about the social mechanisms driving the denunciations. Although denunciation should depend only on who is guilty and not on who has said what up to that point, Grund’s study finds evidence in support of a number of relational mechanisms influencing the denunciation process. Grund argues that the apparent influence of past denunciations on testimonies reveals the limits of the inquiry process itself and what it can reveal about a scandal. This article reviews Grund’s talk and puts the work in a broader context of using approaches rooted in event history modelling and social network theory to illuminate the processes defining social interaction data. It highlights ways in which the keynote can inform the development of computational social science approaches to analysing such data, and argues that the value of such an analysis has implications for scholarship beyond the social sciences.
期刊介绍:
EPJ Data Science covers a broad range of research areas and applications and particularly encourages contributions from techno-socio-economic systems, where it comprises those research lines that now regard the digital “tracks” of human beings as first-order objects for scientific investigation. Topics include, but are not limited to, human behavior, social interaction (including animal societies), economic and financial systems, management and business networks, socio-technical infrastructure, health and environmental systems, the science of science, as well as general risk and crisis scenario forecasting up to and including policy advice.