TY - Generic T1 - An Exploratory Study on the Generation and Distribution of Geotagged Tweets in Nepal T2 - 2018 IEEE 3rd International Conference on Computing, Communication and Security (ICCCS) Y1 - 2018 A1 - B. Devkota A1 - H. Miyazaki KW - active user locations KW - clustering KW - Conferences KW - data mining KW - geotagged tweets KW - hotspots KW - human information behaviors KW - Kernel KW - live human sensors KW - Media KW - microblogging platform KW - Nepal KW - pattern clustering KW - Security KW - social media KW - social media platforms KW - social networking (online) KW - spatial clustering KW - spatial distribution KW - spatial patterns KW - spatial penetration KW - spatiotemporal patterns KW - spatiotemporal public opinion KW - time data KW - travel industry KW - tweet clusters KW - Twitter KW - twitter activities KW - twitter data KW - Urban areas KW - world wide web today AB - 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. JF - 2018 IEEE 3rd International Conference on Computing, Communication and Security (ICCCS) ER -