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Visualization of Twitter Sentiments on Kashmir Territorial Conflict
Cybernetics and Systems ( IF 1.7 ) Pub Date : 2021-07-19 , DOI: 10.1080/01969722.2021.1949520
Shubhangi Rastogi 1 , Divya Bansal 1
Affiliation  

Abstract

This paper aims to showcase the sentiments of Twitter users on the Kashmir conflict, which is an unresolved territorial conflict between two countries, India and Pakistan. Sixty thousand (60k) tweets have been collected using popular keywords posted by users living in the two involved countries and conflicting state. We proposed a twofold adaptive approach to exploit and compare different sentiment analysis techniques, namely lexicons (VADER and NRC) and machine learning. The analysis brings out that positive sentiments are higher in both the involved countries. However, there is a belief that people of both countries are negative and vicious about this act. The observations may help to break this myth and to foster positive engagement between the two nations, which are at the edge of a full-fledged war. The study provides a list of top Twitter influencer handles in each country and the disputed state. Thus, the purpose of this research is to scientifically analyze the situation to arrive at a fair decision and thereby removing unjust opinions that cause a lot of disturbance. This research can be used as fundamental to visualize the extensive insights of a critical event and help in identifying the groups which try to incite users on Twitter.



中文翻译:

关于克什米尔领土冲突的 Twitter 情绪的可视化

摘要

本文旨在展示 Twitter 用户对克什米尔冲突的看法,克什米尔冲突是印度和巴基斯坦两国之间尚未解决的领土冲突。使用居住在两个相关国家和冲突国家的用户发布的流行关键词收集了六万 (60k) 条推文。我们提出了一种双重自适应方法来利用和比较不同的情感分析技术,即词典(VADER 和 NRC)和机器学习。分析表明,所涉及的两个国家的积极情绪都较高。然而,有一种观点认为,两国人民对这一行为持消极和恶毒的态度。观察结果可能有助于打破这个神话,促进两国之间的积极接触,两国正处于全面战争的边缘。该研究提供了每个国家和有争议国家的顶级 Twitter 影响者处理列表。因此,这项研究的目的是科学地分析情况,以做出公平的决定,从而消除引起大量干扰的不公正意见。这项研究可以用作可视化关键事件的广泛见解的基础,并有助于识别试图在 Twitter 上煽动用户的群体。

更新日期:2021-07-19
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