利用Naïve贝叶斯准备Covid -19标注数据

Dipankar Das, Akash Ghosh, Adityar Rayala, Dibyajyoti Dhar, Vidit Sarkar, Avishek Garain, Sourav Kumar
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引用次数: 0

摘要

持续的大流行病打开了潘多拉的盒子,其中包含了社会多年来一直隐藏的大量隐藏问题。但是,目前情况的积极方面是为在全球舞台上解决这些问题提供了机会。其中一个领域被各种不同的情绪所淹没,来自世界各地的人们的反应,就是推特,这是一个微博平台。与过去任何其他事件不同,与冠状病毒相关的标签已经流行了许多天。我们的实验主要以朴素贝叶斯算法为核心,根据这些推文可能属于的不同关键词,对这些推文进行收集、标记和分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Preparing Annotated Data on Covid -19 by Employing Naïve Bayes
The on-going pandemic has opened the pandora’s box of the plethora of hidden problems which the society has been hiding for years. But the positive side to the present scenario is the opening up of opportunities to solve these problems on the global stage. One such area which was being flooded with all kinds of different emotions, and reaction from the people all over the world, is twitter, which is a micro blogging platform. Coronavirus related hash tags have been trending all over for many days unlikeany other event in the past. Our experiment mainly deals with the collection, tagging and classification of these tweets based on the different keywords that they may belong to, using the Naive Bayes algorithm atthe core.
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