大数据与新闻传播研究的学术想象  

Academic Discussion on Big Data in Journalism and Communication Research

作　　者：张志安[1,2] ZHANG Zhian(Professor and Dean in the School of Communication and Design at Sun Yat-sen Universit)

机构地区：[1]中山大学传播与设计学院 [2]广东省舆情大数据分析与仿真重点实验室,广州大数据与公共传播研究基地

出　　处：《国际新闻界》2018年第2期133-139,共7页Chinese Journal of Journalism & Communication

基　　金：本文是教育部哲学社科研究重大课题攻关项目“大数据时代国家意识形态安全风险与防范体系构建研究”(编号16JZD006).

摘　　要：本文从理论取向和应用取向的维度回顾大数据与新闻传播的相关研究,发现基于大数据的新闻传播研究多数是"数据驱动"的研究、而非"理论驱动"的研究,研究方法上主要采用基于词典的文本分析、机器学习和复杂社会网络分析等,此外,相关研究更多注重的是变量之间相关关系的检验,而非因果关系的阐释。最后,本文针对大数据给新闻传播研究带来的学术想象,提出相关研究需要处理好三个关系,即:处理好"理论驱动"和"数据驱动"的关系,处理好学术前沿问题和中国本土问题的关系,处理好网络空间数据和现实社会公共数据的关系。This article reviews the research on big data as well as journalism and communication from the theory-driven and practice-driven perspectives. According to the reviews, most journalism and communication studies based on the big data approach are data-driven instead of theory- driven. Moreover, these studies usually used the following research methods： dictionary-based text analysis, matching learning, social network analysis, etc. Besides, most relevant studies focus on the correlations between different variables rather than the causality. Finally, the article indicates that to improve the application of big data in journalism and communication research, three relationships should be addressed： the relationship between theory-driven approach and data-driven approach, the relationship between academic frontier issues and Chinese-indigenous issues, and the relationship between online data and offline data.

关 键 词：社交媒体 理论驱动 数据驱动 多雏空间传播 

分 类 号：G210.7[文化科学—新闻学]