基于 OWA 的多维度推特数据分析框架:COVID-19 期间公民-政府参与案例研究

IF 1 4区 计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Ankit Gupta, Sarabjeet Singh, Harmesh Rana, Vinay Kumar Prashar, Rajan Yadav
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引用次数: 0

摘要

在这场由冠状病毒引发的全球大流行中,社交媒体在传播有关大流行各方面的意识和准确无误的新闻方面发挥着至关重要的作用。世界各国政府都在不断利用现有的社交媒体平台向公众有效传达危机信息,最终使公民了解当前的状况。本研究系统地调查了印度政府机构如何在 COVID 19 危机期间利用社交媒体平台 Twitter 传播相关信息,并与公民取得联系。这些 twitter 数据来自不同政府官员的官方 Twitter 账户,涵盖了多日来的各种参数。为了聚合和汇总这些多维数据并对其进行进一步处理,本研究引入了一种基于聚类和有序加权算子的新型多标准决策框架。自上世纪 90 年代末引入有序加权运算符以来,许多有序加权运算符已被成功用于许多领域的汇总目的。该框架输出的汇总值可用于分析政府对 COVID 19 情况的各种参数响应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An OWA Based MCDM Framework for Analyzing Multidimensional Twitter Data: A Case Study on the Citizen-Government Engagement During COVID-19

In this global pandemic caused by coronavirus, the role of social media is found to be vital for spreading awareness and faultless news about various aspects of the pandemic. Governments across the world are constantly using available social media platforms to communicate crisis information efficiently to the public, which ultimately making citizens aware about the prevailing conditions. This study systematically investigates how Indian government agencies used social media platform-Twitter to disseminate the relevant information, and to reach out to the citizens during COVID 19 crisis. Spread across various parameters over many days, the twitter data was scrapped from the official Twitter accounts of different government officials. To aggregate and summarize this multi-dimensional data and to process it further, a novel multi-criteria decision making based framework that makes the use of Clustering and Ordered weighted operators is being introduced in this study. Many OWA operators have been introduced in the recent past after their introduction in late 90s, and are used successfully for aggregation purposes in many domains. The summarized values received as an output of the framework are then used to analyze the government response towards COVID 19 situation across various parameters.

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来源期刊
CiteScore
2.70
自引率
0.00%
发文量
48
审稿时长
13.5 months
期刊介绍: The International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems is a forum for research on various methodologies for the management of imprecise, vague, uncertain or incomplete information. The aim of the journal is to promote theoretical or methodological works dealing with all kinds of methods to represent and manipulate imperfectly described pieces of knowledge, excluding results on pure mathematics or simple applications of existing theoretical results. It is published bimonthly, with worldwide distribution to researchers, engineers, decision-makers, and educators.
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