新闻散布:社交媒体中的话题相似性

2020 3rd International Conference on Computer Applications & Information Security (ICCAIS) Pub Date : 2020-03-01 DOI:10.1109/ICCAIS48893.2020.9096776

Raja H. Alyaffer, D. Alboaneen, Nourah F. Alqahtani

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引用次数: 0

摘要

使用社交媒体网站(如Twitter)的新闻机构每天都会迅速生成大量数据。数据可视化是一种以图形化方式表示微博数据的有效方法，可以增加对新闻机构在给定时间段内报道内容的理解。本文的重点是可视化随着时间的推移，英语新闻媒体的广泛横截面的推文(Twitter上的帖子)，其目标是开发一个交互式的基于网络的可视化系统，该系统将新闻媒体推文的输出总结为散点图，其中每个点都指一个新闻媒体。这种可视化可以让感兴趣的各方根据特定词汇的使用频率来探索新闻媒体报道的异同。

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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NewsScatter: Topic Similarity in Social Media

News organisations that use social media sites (such as Twitter) rapidly generate a large volume of data every day. Data visualisation is an effective way to represent microblogging data graphically in order to increase understanding of what news organisations are reporting over a given time period. This paper focuses on visualising the tweets (posts on Twitter) of a broad cross-section of English-language news outlets over time, with the goal of developing an interactive web-based visualisation system that summarises the output of news outlets’ tweets as a scatter plot where each point refers to a news outlet. Such a visualisation could enable interested parties to explore similarities and differences among what news outlets report based on the frequency with which specific words are used.

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2020 3rd International Conference on Computer Applications & Information Security (ICCAIS)

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