Analyses of Geo-Referenced Twitter Data for Understanding Spatial Distribution and Content Classification
Nikola Dzakovic, Nikola Dinkic, Jugoslav Jokovic, Leonid Stoimenov, Dejan Rancic
International Journal of Computational Linguistics Research, Vol. 12, No. 2, 2021.
DOI: https://doi.org/10.6025/jcl/2021/12/2/35-42
Link: https://www.dline.info/jcl/fulltext/v12n2/jclv12n2_1.pdf
Abstract:
We intend to study the spatial patterns of the urban regions and design it for open spaces. To do so we have employed the user-generated twitter data that could support and improve the understanding. The features such as temporal and spatial distribution, content classification, language determination and sentiment analyses are studied using the data generated by Twitter social network. We have sued the Twitter search engine application to classify and process the geo-referenced tweets collected.