Abstract

After radio and television, online media are fast becoming a primary source of information for many Africans. With this increase, it is becoming necessary for media researchers to explore ways to better understand production, content and reception patterns of online news in the continent. This paper introduces freely available tools for systematic and (semi-)automated collection, storage and analysis of digital news that builds on recent advances in the computational power of personal computers, and the decreasing costs of storing large amounts of data. I start by describing existing challenges in the collection of online news text data, including the limited amount of African news content in commercial databases, and the methodological shortcomings of using commercial search engines. Then, I present a four-stage approach using packages written in the open-source R programming language to automate the collection of online news content (web scraping); transform this content for easier storage and analysis (data processing); use computational text analysis tools to describe and categorise data; and present the results in ways that are easier to understand (data visualisation). The paper concludes with a summary of recommendations for using computational methods to study African communication phenomena.

摘要

在广播和电视之后，在线媒体正迅速成为许多非洲人的主要信息来源。随着这一增长，媒体研究人员有必要探索更好地了解非洲大陆在线新闻的产生，内容和接收方式的方法。本文介绍了可免费使用的工具，该工具基于对个人计算机的计算能力的最新进展以及存储大量数据的成本不断降低的情况，对数字新闻进行了系统的（半）自动化的收集，存储和分析。我首先描述在线新闻文本数据收集中的现有挑战，包括商业数据库中非洲新闻内容的数量有限，以及使用商业搜索引擎的方法学缺陷。然后，我提出了一种四阶段的方法，该方法使用以开源R编程语言编写的软件包来自动收集在线新闻内容（抓取网络）；转换此内容以便于存储和分析（数据处理）；使用计算文本分析工具来描述和分类数据；并以更易于理解的方式呈现结果（数据可视化）。本文最后总结了使用计算方法研究非洲交流现象的建议。