An Exploratory Study on the Generation and Distribution of Geotagged Tweets in Nepal

B. Devkota, H. Miyazaki
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引用次数: 4

Abstract

Social media platforms contribute a huge part of the content available on the world wide web today. These platforms act as a rich source of real time data from live human sensors. These media disseminate spatiotemporal public opinion regarding a range of events, activities and human information behaviors. This paper explores the active user locations and spatial penetration of popular microblogging platform, Twitter, in Nepal. A heatmap visualization is used to show the intensity and distribution of the spatial patterns of Twitter activities in different parts of Nepal. Clustering is a popular technique for knowledge discovery, so spatial clustering is applied to groups tweets spatially into different classes. Such spatial clustering helps in the identification of areas of similar twitter activities and shows the distribution of the spatial patterns in different parts of Nepal. Tweet clusters are observed mainly in the main cities and the tourism centers. Further, an examination of the twitter data shared by the local Nepalese people and the foreigners are shown. This study contributes the research line by providing insights to better understand the spatiotemporal patterns and hotspots of tweets in Nepal. Such patterns and hotspots have an immense practical value that can be attributable to a place in order to derive meaningful insights related to various domains like a disease, crime, tourism, etc.
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尼泊尔地理标记推文生成与分布的探索性研究
社交媒体平台贡献了当今万维网上可用内容的很大一部分。这些平台是实时人体传感器实时数据的丰富来源。这些媒介传播关于一系列事件、活动和人类信息行为的时空舆论。本文探讨尼泊尔流行的微博平台Twitter的活跃用户位置和空间渗透率。可视化热图用于显示尼泊尔不同地区Twitter活动的强度和空间分布模式。聚类是一种流行的知识发现技术,因此空间聚类可以将推文在空间上划分为不同的类。这种空间聚类有助于识别类似twitter活动的区域,并显示了尼泊尔不同地区的空间模式分布。微博集群主要分布在主要城市和旅游中心。此外,本文也检视尼泊尔本地人与外国人分享的推特资料。本研究为更好地理解尼泊尔推文的时空格局和热点提供了见解,为研究提供了线索。这些模式和热点具有巨大的实用价值,可以归因于一个地方,以便获得与疾病、犯罪、旅游等各个领域相关的有意义的见解。
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