Spatial Point Data Analysis of Geolocated Tweets in the First Day of Eid Al-Fitr 2017 in Java Island

5th Geoinformation Science Symposium 2017

地球科学;计算机科学

Wibowo, T.W.^1

Faculty of Geography, Universitas Gadjah Mada, Indonesia^1

关键词: Geolocated Tweet;    Location information;    Location sensors;    Pattern analysis;    Python programming language;    Spatial points;    Text data mining;    Twitter;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/98/1/012032/pdf
DOI  :  10.1088/1755-1315/98/1/012032

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

Eid Al-Fitr is a worldwide Muslim feast day, which in Indonesia generally accompanied by tradition of going home (mudik). The demographic patterns at the time of the holiday are generally shifted, in which some urban residents will travel to their hometowns. The impact of this shifting is that there is a quite massive mobility of the population, which is generally accompanied by traffic congestion. The presence of location sensors on smartphone devices, open the opportunity to map the movement of the population in realtime or near-realtime. Especially now that social media applications have been integrated with the capability to include location information. One of the popular social media applications in Indonesia is Twitter, which provides microblogging facilities to its users. This study aims to analyze the pattern of Geolocated Tweets data uploaded by Twitter users on the first day of Eid Al-Fitr (1 Syawal 1438H). Geolocated Tweets data mining is done by using Streaming API (Application Programming Interface) and Python programming language. There are 13,224 Geolocated Tweets points obtained at the location of the study. Various point data analysis techniques applied to the data have been collected, such as density analysis, pattern analysis, and proximity analysis. In general, active Twitter users are dominated by residents in major cities, such as Jakarta, Bandung, Surabaya, Yogyakarta, Surakarta and Semarang. The results of the analysis can be used to determine whether the Geolocated Tweets data mined by the Streaming API method can be used to represent the movement of the population when mudik.