社会媒体的质量评估:从文献中吸取的教训

A. Arroyo, T. Onorati, P. Díaz
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引用次数: 2

摘要

社交网络是全世界都很感兴趣的话题。年复一年,我们见证了新用户数量的增长,甚至新技术(如增强现实、360度摄像头等)和新社交网络的诞生。然而,这种现象与自动程序(机器人)和假新闻的出现形成鲜明对比,它们会影响发布信息的质量。本文介绍了在不同的社交网络中发现的信息质量的最新状况。此外,我们提出了一系列需要遵循的经验教训,以便开发一个理论应用程序,用于测量给定事件的用户生成信息的质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quality Assessment of Social Media: Lessons Learnt from the Literature
Social networks are a subject of great interest worldwide. Year after year we have experienced an increase in the number of new users and, even, the creation of new technologies (i.e. augmented reality, 360º cameras, …) and new social networks. However, this phenomenon is contrasted with the appearance of automatic programs (bots) and fake news that can affect the quality of published information. This paper presents the state of the art of the quality of the information found in different social networks. In addition, we propose a series of learnt lessons to be followed in order to develop a theoretical application that measures the quality of a user generated information for a given event.
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