JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Keyword Filtering about Disaster and the Method of Detecting Area in Detecting Real-Time Event Using Twitter
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Keyword Filtering about Disaster and the Method of Detecting Area in Detecting Real-Time Event Using Twitter
Ha, Hyunsoo; Hwang, Byung-Yeon;
  PDF(new window)
 Abstract
This research suggests the keyword filtering about disaster and the method of detecting area in real-time event detecting system by analyzing contents of twitter. The diffusion of smart-mobile has lead to a fast spread of SNS and nowadays, various researches based on studying SNS are being processed. Among SNS, the twitter has a characteristic of fast diffusion since it is written in 140 words of short paragraph. Therefore, the tweets that are written by twitter users are able to perform a role of sensor. By using these features the research has been constructed which detects the events that have been occurred. However, people became reluctant to open their information of location because it is reported that private information leakage are increasing. Also, problems associated with accuracy are occurred in process of analyzing the tweet contents that do not follow the spelling rule. Therefore, additional designing keyword filtering and the method of area detection on detecting real-time event process were required in order to develop the accuracy. This research suggests the method of keyword filtering about disaster and two methods of detecting area. One is the method of removing area noise which removes the noise that occurred in the local name words. And the other one is the method of determinating the area which confirms local name words by using landmarks. By applying the method of keyword filtering about disaster and two methods of detecting area, the accuracy has improved. It has improved 49% to 78% by using the method of removing area noise and the other accuracy has improved 49% to 89% by using the method of determinating the area.
 Keywords
Twitter;Real-Time Event Detect;Detecting Area;Keyword Filtering;
 Language
Korean
 Cited by
 References
1.
J. Yim and B. Hwang, "Twitter Based Realtime Event-Location Detector," KIPS Transactions on Software and Data Engineering, Vol.4, No.8, pp.301-308, 2015. crossref(new window)

2.
R. Li, K. H. Lei, R. Khadiwala, and K. Chang, "TEDAS: a Twitter Based Event Detection and Analysis System," Proc. of the IEEE 28th International Conference on Data Engineering, pp.1273-1276, 2012.

3.
X. Zhou and L. Chen, "Event Detection over Twitter Social Media Streams," The VLDB Journal, Vol.23, No.3, pp.381-400, 2014. crossref(new window)

4.
J. Shin and C. Ock, "A Stage Transition Model for Korean Part-of-Speech and Homograph Tagging," Journal of KIISE : Software and Applications, Vol.39, No.11, pp.889-901, 2012.

5.
J. Hur and C. Ock, "A Homonym Disambiguation System based on Semantic Information Extracted from Dictionary Definitions," Journal of KIISE : Software and Applications, Vol.28, No.9, pp.688-698, 2001.

6.
J. Yim, H. Ha, and B. Hwang, The Method for Removing Noises from Event Detection using Twitter," Proc. of KSII Fall Conference, pp.105-106, 2014.

7.
S. Woo and B. Hwang, "Geographical Name Denoising by Machine Learning of Event Detection Based on Twitter," KIPS Transactions on Software and Data Engineering, Vol. 4, No.10, pp.447-454, 2015. crossref(new window)

8.
Twitter Streaming API [Internet], http://dev.twitter.com/docs/streaming-apis.

9.
S. Lee, Lucean Korean Morph Analyzer [Internet], http://cafe.naver.com/korlucene.

10.
Republic of Korea National Statistical Office, Population and Housing Census [Internet], http://www.kostat.go.kr.

11.
Naver Breaking News [internet], http://news.naver.com/main/list.nhn?mode=LSD&mid=sec&sid1=001.