@proceedings {103,
	title = {An Exploratory Study on the Generation and Distribution of Geotagged Tweets in Nepal},
	year = {2018},
	month = {Oct},
	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.},
	keywords = {active user locations, clustering, Conferences, data mining, geotagged tweets, hotspots, human information behaviors, Kernel, live human sensors, Media, microblogging platform, Nepal, pattern clustering, Security, social media, social media platforms, social networking (online), spatial clustering, spatial distribution, spatial patterns, spatial penetration, spatiotemporal patterns, spatiotemporal public opinion, time data, travel industry, tweet clusters, Twitter, twitter activities, twitter data, Urban areas, world wide web today},
	doi = {10.1109/CCCS.2018.8586827},
	author = {B. Devkota and H. Miyazaki}
}
