{"title":"分析媒体效应的出现和持续时间的方法论框架","authors":"Fabian Thomas","doi":"10.1093/joc/jqac013","DOIUrl":null,"url":null,"abstract":"\n Media effects have been studied for decades. However, it is still unclear how to assess the dynamic nature of media effects methodologically and analytically. Building on recent research on media effects and developments in statistical modeling, I present a methodological framework to provide a detailed analysis of media effect dynamics. To do so, I describe general patterns for the appearance and the duration of media effects and present statistical approaches to analyze them. Using artificial data, I illustrate how these statistical approaches can be applied to longitudinal data and show how they behave across different data scenarios. Further, extensions, limitations, and the theoretical contribution of the framework to the field of media effects research are discussed. In sum, the presented framework can be used to test various communication theories and can be combined with many research designs in order to identify patterns in the appearance and duration of media effects.","PeriodicalId":53925,"journal":{"name":"Fonseca-Journal of Communication","volume":"23 1","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2022-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A Methodological Framework for Analyzing the Appearance and Duration of Media Effects\",\"authors\":\"Fabian Thomas\",\"doi\":\"10.1093/joc/jqac013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Media effects have been studied for decades. However, it is still unclear how to assess the dynamic nature of media effects methodologically and analytically. Building on recent research on media effects and developments in statistical modeling, I present a methodological framework to provide a detailed analysis of media effect dynamics. To do so, I describe general patterns for the appearance and the duration of media effects and present statistical approaches to analyze them. Using artificial data, I illustrate how these statistical approaches can be applied to longitudinal data and show how they behave across different data scenarios. Further, extensions, limitations, and the theoretical contribution of the framework to the field of media effects research are discussed. In sum, the presented framework can be used to test various communication theories and can be combined with many research designs in order to identify patterns in the appearance and duration of media effects.\",\"PeriodicalId\":53925,\"journal\":{\"name\":\"Fonseca-Journal of Communication\",\"volume\":\"23 1\",\"pages\":\"\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2022-05-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Fonseca-Journal of Communication\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/joc/jqac013\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMMUNICATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fonseca-Journal of Communication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/joc/jqac013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMMUNICATION","Score":null,"Total":0}
A Methodological Framework for Analyzing the Appearance and Duration of Media Effects
Media effects have been studied for decades. However, it is still unclear how to assess the dynamic nature of media effects methodologically and analytically. Building on recent research on media effects and developments in statistical modeling, I present a methodological framework to provide a detailed analysis of media effect dynamics. To do so, I describe general patterns for the appearance and the duration of media effects and present statistical approaches to analyze them. Using artificial data, I illustrate how these statistical approaches can be applied to longitudinal data and show how they behave across different data scenarios. Further, extensions, limitations, and the theoretical contribution of the framework to the field of media effects research are discussed. In sum, the presented framework can be used to test various communication theories and can be combined with many research designs in order to identify patterns in the appearance and duration of media effects.