Social Network Analysis to Surveillance the Impact of Covid-19 in the African continent

被引：0

作者：

Edinson Chire Saire, Josimar ^{[1
]}

Egbon, Osafu Augustine ^{[1
]}

Belachew, Asrat Mekonnen ^{[2
]}

机构：

[1] Univ Sao Paulo, Inst Math & Comp Sci ICMC, Sao Carlos, SP, Brazil

[2] Ambo Univ, Dept Math, Ambo, Ethiopia

来源：

INTERNATIONAL CONFERENCE ON ELECTRICAL, COMPUTER AND ENERGY TECHNOLOGIES (ICECET 2021) | 2021年

关键词：

Text Mining; Twitter Analytics; Coronavirus; Covid-19; Africa; INFLUENZA; EPIDEMIOLOGY; MEDIA; TOOL;

D O I：

10.1109/ICECET52533.2021.9698713

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Pandemics originated by Covid-19 has caused many reactions in the world. Each country has reacted with different health policies. In this work, we analyze the publications of African citizens on Social networks (Twitter) to understand the pandemic scenario during the study period using a text mining approach. The study also adopted a statistical model to quantify the impact of daily COVID-19 cases on the frequency of tweets. Findings show that African tweets are related to awareness creation and policies to control the spread of COVID-19.

引用

页码：648 / 653

页数：6

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