An Exploratory Study on the Generation and Distribution of Geotagged Tweets in Nepal
- 1 October 2018
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 70-76
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
This publication has 17 references indexed in Scilit:
- Eyewitness2015
- Development of 2010 national land cover database for the NepalJournal of Environmental Management, 2015
- A geocomputational analysis of Twitter activity around different world citiesGeo-spatial Information Science, 2014
- Major Life Event Extraction from Twitter based on Congratulations/Condolences Speech Acts2014
- Landmark-based user location inference in social media2013
- Spatiotemporal anomaly detection through visual analysis of geolocated Twitter messages2012
- On social Web sitesInformation Systems, 2010
- Analysis of geographic queries in a search engine log2008
- Citizens as sensors: the world of volunteered geographyGeoJournal, 2007
- Local Indicators of Spatial Association—LISAGeographical Analysis, 1995