社会科学和计算机辅助的故事:数据新闻教学逻辑初探

Social Sciences and Computer-mediated Story-telling:An Inquiry into the Logic of Data Journalism Pedagogy

数据新闻的选题除了考虑新闻特性之外,还涉及社会科学研究中的概念化与操作化,它们将指导内容生产者在收集数据之前,细致地规划方向,以获取信度和效度较高的数据;在数据鉴别的过程中,数据素养与统计分析思维同时在起作用;清理数据的过程即根据主题,发现异常值、对数据和变量进行选择、计算、转换和分类的过程;分析数据主要涉及描述统计和推断统计等过程;根据主题和数据特征,结果的展示主要包括从数据到图表、地图和网络三大类数据可视化的过程。最后,基于对数据的分析和对社会的理解,开发与读者互动的功能,基于数据讲故事。数据新闻强调学生的参与和实践,共同探索概念化、操作化、信息搜索、信息分类、数据展示、关系展示、时空展示、网络展示,直至数据新闻作品的生产。基于上述过程,本文提出数据新闻的"概念-现象、人群-社区、时间-空间、网络-关系、互动—故事"十元素模型。

In addition to considering news features, the topics of data journalization involve conceptualization and manipulation in social science research. They will guide content producers to carefully plan their direction before data collection to obtain reliability and validity. The process of data cleaning is the process of selecting, calculating, transforming and classifying the data and variables according to the theme, discovering the outliers, and the process of data analysis and data analysis. In the process of data identification, data literacy and statistical analysis thinking are working together. The analysis data mainly involves the process of description statistics and inferential statistics. According to the theme and data characteristics, the result display includes the process of data visualization from data to chart, map and network. Finally, based on the data analysis and understanding of the community, the development of interaction with the reader function, based on data storytelling. Data News emphasizes student participation and practice, to explore the conceptualization, operation, information search, information classification, data display, relationship display, space-time display, network display, until the data news production. Based on the above process, this paper presents the ten-element model of ＂concept-phenomenon, crowd-community, time-space, network-relationship, interaction-story＂.