Unraveling China’s digital traces: evaluating communication scholarship through a sociotechnical lens

社会技术系统 奖学金 学术交流 观点 跟踪(心理语言学) 数字奖学金 社会学 数据科学 计算机科学 知识管理 政治学 公共关系 图书馆学 法学 艺术 语言学 哲学 出版 视觉艺术
作者
Kaiping Chen,Yingdan Lu,Yiming Wang
出处
期刊:Chinese Journal of Communication [Taylor & Francis]
卷期号:: 1-24 被引量:1
标识
DOI:10.1080/17544750.2023.2264406
摘要

AbstractIn the growing trend of research using digital trace data to study human activities and opinions across different contexts, networked China has emerged as a prominent area of interest. However, research that critically examines the use, strengths, and weaknesses of existing digital trace methods, and the extent to which they can reveal the true landscape of digital China remains limited. To address these gaps, this study proposes a framework for examining and evaluating the knowledge production of digital trace research within a sociotechnical system comprising state actors, platform governance, digital civil society, and international forces. We then provide the first empirical examination of the knowledge claims and epistemic approaches used in digital trace communication scholarship that has studied China across different phases in the past 30 years. Grounded in the resulting empirical evidence, we discuss two common practices in existing digital trace research on China, how these approaches and perspectives could affect the validity and reliability of offering diverse viewpoints for studying and understanding digital China, and directions for improving these practices.Keywords: Digital traceknowledge productionevidence-driven approachChinasociotechnical systemcomputational social science AcknowledgmentsWe would like to thank Steve Meyer, the data strategist from the University of Wisconsin–Madison Libraries, for helping us retrieve data from the Web of Science database. We are also grateful to Wenhong Chen, Zhongdang Pan, Stephen D. Reese, the anonymized reviewers, and the participants from the National Communication Association 107th Annual Convention for providing feedback at different stages of this project.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by University of Wisconsin Madison, the Wisconsin Alumni Research Foundation.Notes on contributorsKaiping ChenKaiping Chen (PhD, Stanford University) is an assistant professor in computational communication at the Department of Life Sciences Communication, University of Wisconsin–Madison. Her research interests are public deliberation, science communication, and computational social science, and she has published in journals such as the Journal of Communication, Journal of Computer-Mediated Communication, New Media & Society, The American Political Science Review, Public Opinion Quarterly, and PNAS.Yingdan LuYingdan Lu (PhD, Stanford University) is an assistant professor in the Department of Communication Studies at Northwestern University. Her research focuses on digital technology, political communication, and information manipulation in authoritarian and democratic contexts using computational and qualitative methods. Her work has appeared in peer-reviewed journals, such as Political Communication, New Media & Society, Human–Computer Interaction, and Computational Communication Research.Yiming WangYiming Wang is a PhD candidate in mass communications at the School of Journalism and Mass Communication, University of Wisconsin–Madison. Her research focuses on the interplay between information ecology, identity politics, and other political attitudes and behaviors.
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