Jeong-Nam Kim, Ming Ming Chiu, Hyelim Lee, Yu Won Oh, Homero Gil de Zúñiga, Chong Hyun Park
{"title":"绘制媒体研究范式:新闻与大众传播季刊》的科学演变世纪","authors":"Jeong-Nam Kim, Ming Ming Chiu, Hyelim Lee, Yu Won Oh, Homero Gil de Zúñiga, Chong Hyun Park","doi":"10.1177/10776990231213376","DOIUrl":null,"url":null,"abstract":"This retrospective review of nearly a century of publications in Journalism and Mass Communication Quarterly (JMCQ) traces the maturation of media studies toward a scientific discipline. The field’s dominant paradigms—media effects and communicator uses—persist, adapt, and diversify over time, yielding actionable insights. Challenges include (a) bridging older and newer media theories, (b) harnessing data science, and (c) capitalizing on artificial intelligence/machine learning (AI/ML). Future media research can conceptualize evolving three-dimensional interactions among media, people, and AI. We propose seven initiatives for the next century: revisiting classical theories, fostering interdisciplinary collaboration, balancing descriptive and prescriptive theorization, nurturing indigenous theorizing, collaborating with industry, reverse theorizing with AI, and exploring and regulating AI’s role in media.","PeriodicalId":48095,"journal":{"name":"Journalism & Mass Communication Quarterly","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Mapping Media Research Paradigms: Journalism & Mass Communication Quarterly’s Century of Scientific Evolution\",\"authors\":\"Jeong-Nam Kim, Ming Ming Chiu, Hyelim Lee, Yu Won Oh, Homero Gil de Zúñiga, Chong Hyun Park\",\"doi\":\"10.1177/10776990231213376\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This retrospective review of nearly a century of publications in Journalism and Mass Communication Quarterly (JMCQ) traces the maturation of media studies toward a scientific discipline. The field’s dominant paradigms—media effects and communicator uses—persist, adapt, and diversify over time, yielding actionable insights. Challenges include (a) bridging older and newer media theories, (b) harnessing data science, and (c) capitalizing on artificial intelligence/machine learning (AI/ML). Future media research can conceptualize evolving three-dimensional interactions among media, people, and AI. We propose seven initiatives for the next century: revisiting classical theories, fostering interdisciplinary collaboration, balancing descriptive and prescriptive theorization, nurturing indigenous theorizing, collaborating with industry, reverse theorizing with AI, and exploring and regulating AI’s role in media.\",\"PeriodicalId\":48095,\"journal\":{\"name\":\"Journalism & Mass Communication Quarterly\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2023-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journalism & Mass Communication Quarterly\",\"FirstCategoryId\":\"98\",\"ListUrlMain\":\"https://doi.org/10.1177/10776990231213376\",\"RegionNum\":2,\"RegionCategory\":\"文学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMMUNICATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journalism & Mass Communication Quarterly","FirstCategoryId":"98","ListUrlMain":"https://doi.org/10.1177/10776990231213376","RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMMUNICATION","Score":null,"Total":0}
引用次数: 3
摘要
这篇对《新闻与大众传播季刊》(Journalism and Mass Communication Quarterly,JMCQ)近一个世纪的出版物进行回顾的文章追溯了传媒研究向科学学科发展的成熟历程。该领域的主导范式--媒体效果和传播者的使用--随着时间的推移而持续、适应和多样化,并产生了可操作的见解。面临的挑战包括:(a)连接新旧媒体理论;(b)利用数据科学;(c)利用人工智能/机器学习(AI/ML)。未来的媒体研究可以将媒体、人和人工智能之间不断发展的三维互动概念化。我们为下个世纪提出了七项倡议:重温经典理论、促进跨学科合作、平衡描述性和规范性理论化、培育本土理论化、与行业合作、与人工智能反向理论化,以及探索和规范人工智能在媒体中的作用。
Mapping Media Research Paradigms: Journalism & Mass Communication Quarterly’s Century of Scientific Evolution
This retrospective review of nearly a century of publications in Journalism and Mass Communication Quarterly (JMCQ) traces the maturation of media studies toward a scientific discipline. The field’s dominant paradigms—media effects and communicator uses—persist, adapt, and diversify over time, yielding actionable insights. Challenges include (a) bridging older and newer media theories, (b) harnessing data science, and (c) capitalizing on artificial intelligence/machine learning (AI/ML). Future media research can conceptualize evolving three-dimensional interactions among media, people, and AI. We propose seven initiatives for the next century: revisiting classical theories, fostering interdisciplinary collaboration, balancing descriptive and prescriptive theorization, nurturing indigenous theorizing, collaborating with industry, reverse theorizing with AI, and exploring and regulating AI’s role in media.
期刊介绍:
Journalism & Mass Communication Quarterly focuses on research in journalism and mass communication. Each issue features reports of original investigation, presenting the latest developments in theory and methodology of communication, international communication, journalism history, and social and legal problems. Journalism & Mass Communication Quarterly also contains book reviews. Refereed. Published four times a year.