使用基于词典的方法可视化新闻Feed数据

2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT) Pub Date : 2018-04-01 DOI:10.1109/ICICCT.2018.8473244

Pujitha Appasani, M. Latha

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引用次数: 0

摘要

现在，人们喜欢在线阅读新闻文章。新闻文章来自远距离的非正式交流目的地。网络网站上的新闻文章的问题是我们无法判断新闻的真假。我们运用不同的技巧来确定新闻文章的极端性。文章的极值是使用基于词典的方法计算的。我们利用假设分数来决定极端，并将新闻文章安排为真实，虚假或无党派。因此，对在线网络内容的意见审查可能会对各种协会，特别是在安全和法律实施部门产生积极影响。本文展示了另一个基于字典的概念调查计算，该计算已经计划与基本焦点正在进行的Twitter内容检查。

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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Visualization of News Feed Data using Lexicon-based Approach

Presently these days people enjoy reading online news articles. The news articles come from long range informal communication destinations. The issue with the news articles in the online networking sites is that we can't decide whether the news is genuine or counterfeit. We apply different techniques to determine the extremity of the news article. The extremity of the article is calculated using the lexicon-based approaches. We utilize the assumption score to decide the extremity and arrange the news articles as genuine, phony or nonpartisan. Thusly, opinion examination of online networking substance might be of enthusiasm for various associations, particularly in security and law implementation segments. This paper displays another dictionary based notion investigation calculation that has been planned with the fundamental spotlight on-going Twitter content examination.

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来源期刊

2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT)

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