{"title":"Quantifying Emotional Flow: Testing the Emotional Flow Hypothesis from a Longitudinal Latent Growth Curve (LGC) Modeling Approach","authors":"Lijiang Shen, S. Li","doi":"10.1080/15213269.2022.2156886","DOIUrl":null,"url":null,"abstract":"ABSTRACT This paper presents a longitudinal, latent growth curve (LGC) modeling approach to refine the emotional flow measure and hypothesis testing. Emotional flow is operationalized as the marked within-individuals variations in one or more discrete emotions over time, which can be modeled as the amount and shape of change in emotions during message exposure. Emotional flow effects are tested in the LGC framework using data collected from a web-based experimental study where individuals (US Qualtrics Panel, N = 620) read an anti-sugary sweetened beverage message in the standard threat appeal format. Simultaneous fear and hope flows were established with unconditional LGC modeling. The two flows and their interaction were then used to predict message effects outcomes. Results showed that flow effects were nonsignificant when either the fear flow or the hope flow was relatively flat in form, but robust when both emotional flows were with marked variations over the course of message exposure.","PeriodicalId":47932,"journal":{"name":"Media Psychology","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Media Psychology","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1080/15213269.2022.2156886","RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMMUNICATION","Score":null,"Total":0}
引用次数: 0
Abstract
ABSTRACT This paper presents a longitudinal, latent growth curve (LGC) modeling approach to refine the emotional flow measure and hypothesis testing. Emotional flow is operationalized as the marked within-individuals variations in one or more discrete emotions over time, which can be modeled as the amount and shape of change in emotions during message exposure. Emotional flow effects are tested in the LGC framework using data collected from a web-based experimental study where individuals (US Qualtrics Panel, N = 620) read an anti-sugary sweetened beverage message in the standard threat appeal format. Simultaneous fear and hope flows were established with unconditional LGC modeling. The two flows and their interaction were then used to predict message effects outcomes. Results showed that flow effects were nonsignificant when either the fear flow or the hope flow was relatively flat in form, but robust when both emotional flows were with marked variations over the course of message exposure.
期刊介绍:
Media Psychology is an interdisciplinary journal devoted to publishing theoretically-oriented empirical research that is at the intersection of psychology and media communication. These topics include media uses, processes, and effects. Such research is already well represented in mainstream journals in psychology and communication, but its publication is dispersed across many sources. Therefore, scholars working on common issues and problems in various disciplines often cannot fully utilize the contributions of kindred spirits in cognate disciplines.