Home > Published Issues > 2021 > Volume 12, No. 4, November 2021 >

Microblog Entity Detection for Natural Disaster Management

Wannapa Phopli 1, Maleerat Maliyaem 1, Choochart Haruechaiyasak 1, and Hathairat Ketmaneechairat 2
1. Department of Information Technology and Digital Innovation, KMUTNB, Bangkok, Thailand
2. The College of Industrial Technology, KMUTNB, Bangkok, Thailand

Abstract—The information from social network can be used to report crisis situation especially natural disaster events. This paper aims to present the utilization of information from twitter in the natural disaster event topic in order to detect the place of event that occurred base on Named Entity Recognition (NER). The place will extract from microblog – Twitter using three techniques: Degree, Betweeness, and Closeness Centrality and then using majority vote for the end of result. In preprocessing step, data only Thai language was collected from twitter using #hagibis in the topic of Super Typhon Hagibis blowing in Japan. Then using three techniques as mention to select only top 5 of words that related to the event. The experimental result show that the word “Japan, ญี่ปุ่น” is the first word of three methods (Degree, Betweenness, Closeness Centrality) with score of 0.57, 0.55, and 0.65 respectively It showed that the message from twitter can be trusted and indicated the event location.
 
Index Terms—Twitter message analysis, microblog analysis, entity detection

Cite: Wannapa Phopli, Maleerat Maliyaem, Choochart Haruechaiyasak, and Hathairat Ketmaneechairat, "Microblog Entity Detection for Natural Disaster Management," Journal of Advances in Information Technology, Vol. 12, No. 4, pp. 351-356, November 2021. doi: 10.12720/jait.12.4.351-356

Copyright © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.