Digital Journalism, Drones, and Automation
Digital Journalism, Drones, and Automation
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数字新闻、无人机和自动化
DOI：
10.1093/oso/9780190655860.001.0001
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
C. Dowd
中科院分区：
文献类型：
--
作者：
C. Dowd
在线技术和新闻系统的进步，例如跨数字资源的自动推理以及与云服务器的存储和软件连接，已经改变了数字新闻的制作和出版方法。编辑使用的集成媒体系统也是搜索系统和社交媒体的渠道，但大数据的诱惑和假新闻的增加，以及对分析的投资和验证地点的转变，使新闻业的某些层面变得支离破碎。数据催生了利用数据洞察和机器学习方法的新角色，但获取大数据和数据湖的重要性如此之大，以至于在媒体大亨和社交媒体企业家之间催生了具有新闻价值的合作伙伴关系。然而，数字新闻甚至没有自己的语义系统来保护新闻价值，而是依赖于其他系统的可供性。在新闻中定义明确的词汇和概念的索引和分类系统中，数据泄露和元数据给新闻业带来了挑战。相比之下，数据可视化和实时现场报告与短格式移动媒体和民用无人机在欧洲寻求庇护者危机期间设定了新标准。用无人机进行空中拍摄也增加了新闻学的本体论基础。新闻本体和交叉本体可以为新语义学习系统的设计提供信息。语义CAT方法借鉴了参与式设计和游戏设计，也有助于具有情感属性的合成玩家的概念设计，从而形成学习的元模型。还讨论了保护冲突地区记者的情境感知传感器系统的设计。
Advances in online technology and news systems, such as automated reasoning across digital resources and connectivity to cloud servers for storage and software, have changed digital journalism production and publishing methods. Integrated media systems used by editors are also conduits to search systems and social media, but the lure of big data and rise in fake news have fragmented some layers of journalism, alongside investments in analytics and a shift in the loci for verification. Data has generated new roles to exploit data insights and machine learning methods, but access to big data and data lakes is so significant it has spawned newsworthy partnerships between media moguls and social media entrepreneurs. However, digital journalism does not even have its own semantic systems that could protect the values of journalism, but relies on the affordances of other systems. Amidst indexing and classification systems for well-defined vocabulary and concepts in news, data leaks and metadata present challenges for journalism. By contrast data visualisations and real-time field reporting with short-form mobile media and civilian drones set new standards during the European asylum seeker crisis. Aerial filming with drones also adds to the ontological base of journalism. An ontology for journalism and intersecting ontologies can inform the design of new semantic learning systems. The Semantic CAT Method, which draws on participatory design and game design, also assists the conceptual design of synthetic players with emotion attributes, towards a meta-model for learning. The design of context-aware sensor systems to protect journalists in conflict zones is also discussed.