Labservatory: a synergy between journalism studies and computer science for online news observation

Dimitris Trimithiotis, Iacovos I. Ioannou, V. Vassiliou, Panicos Christou, Stelios Chrysostomou, Erotokritos Erotokritou, Demetris Kaizer
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Abstract

PurposeThis article explores the synergy between journalism studies and computer science in the context of observing online news. By establishing web applications of online media observatories as research tools, researchers can employ various analytical approaches to gain valuable insights into online news discourse and production.Design/methodology/approachDrawing eight months of data (01.08.2022–30.04.2023) from the Labservatory’s web application, i.e. over 250,000 news items, the article demonstrates how some of this web application’s main functionalities may be useful in implementing (1) news flow analysis, (2) news topic distribution analysis and (3) media discourse analysis.FindingsThe capabilities provided by this web application, (1) to simultaneously analyse the daily news production of ten media outlets with varying features, (2) to rapidly collect a large volume of news items, (3) to identify the news categories as classified by the media themselves, (4) to present the results of the search in relevance order and (5) to automatically generate a search report, highlight the significance of this interdisciplinary collaboration for implementing comprehensive analyses of online news.Originality/valueThe article concludes by emphasising the importance of continuing this joint effort, as it opens new avenues for further research and provides a deeper grasp of the intricate relationship between journalism, technology and society in the digital era. The Labservatory also contributes to society since it may be used by the broader public for immediate access to more pluralistic information and thus for promoting both news media literacy and news media accountability.
Labservatory:新闻学研究与计算机科学在网络新闻观察方面的协同作用
本文探讨了新闻学研究与计算机科学在观察网络新闻方面的协同作用。通过建立在线媒体观察站的网络应用程序作为研究工具,研究人员可以采用各种分析方法,获得对在线新闻话语和生产的宝贵见解。文章通过实验室网络应用程序中八个月(2022 年 8 月 1 日至 2023 年 4 月 30 日)的数据,即超过 25 万条新闻,展示了该网络应用程序的一些主要功能如何有助于实施(1)新闻流分析、(2)新闻话题分布分析和(3)媒体话语分析。研究结果该网络应用程序具有以下功能:(1) 同时分析十家媒体的日常新闻生产,这些媒体的特点各不相同;(2) 快速收集大量新闻条目;(3) 识别媒体自己划分的新闻类别;(4) 按相关性顺序显示搜索结果;(5) 自动生成搜索报告。独创性/价值文章最后强调了继续这项合作的重要性,因为它为进一步研究开辟了新的途径,并使人们对数字时代新闻、技术和社会之间错综复杂的关系有了更深入的了解。实验室还对社会做出了贡献,因为广大公众可以利用实验室即时获取更加多元化的信息,从而促进新闻媒体素养的提高和新闻媒体问责制的加强。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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