Local Event Detection Scheme by Analyzing Relevant Documents in Social Networks

In this paper, we propose a local event detection scheme by analyzing relevant documents in social networks to improve the accuracy of event detection. To detect local events by using geographical data, the proposed scheme embeds them using a geographical data dictionary and generates a weighted key...

Full description

Bibliographic Details
Main Authors:	Dojin Choi, Soobin Park, Dongho Ham, Hunjin Lim, Kyoungsoo Bok, Jaesoo Yoo
Format:	Article
Language:	English
Published:	MDPI AG 2021-01-01
Series:	Applied Sciences
Subjects:	social network service event detection relevant documents keyword graph
Online Access:	https://www.mdpi.com/2076-3417/11/2/577

id	doaj-7ec14fc4943e4bdb9290b77085773545
record_format	Article
spelling	doaj-7ec14fc4943e4bdb9290b770857735452021-01-09T00:04:04ZengMDPI AGApplied Sciences2076-34172021-01-011157757710.3390/app11020577Local Event Detection Scheme by Analyzing Relevant Documents in Social NetworksDojin Choi0Soobin Park1Dongho Ham2Hunjin Lim3Kyoungsoo Bok4Jaesoo Yoo5Department of Information and Communication Engineering, Chungbuk National University, Chungdae-ro 1, Seowon-Gu, Cheongju, Chungbuk 28644, KoreaDepartment of Information and Communication Engineering, Chungbuk National University, Chungdae-ro 1, Seowon-Gu, Cheongju, Chungbuk 28644, KoreaDepartment of Information and Communication Engineering, Chungbuk National University, Chungdae-ro 1, Seowon-Gu, Cheongju, Chungbuk 28644, KoreaDepartment of Information and Communication Engineering, Chungbuk National University, Chungdae-ro 1, Seowon-Gu, Cheongju, Chungbuk 28644, KoreaDepartment of SW Convergence Technology, Wonkwang University, Iksandae 460, Iksan, Jeonbuk 54538, KoreaDepartment of Information and Communication Engineering, Chungbuk National University, Chungdae-ro 1, Seowon-Gu, Cheongju, Chungbuk 28644, KoreaIn this paper, we propose a local event detection scheme by analyzing relevant documents in social networks to improve the accuracy of event detection. To detect local events by using geographical data, the proposed scheme embeds them using a geographical data dictionary and generates a weighted keyword graph using social network characteristics. The data left by users in social networks include not only postings but also related documents such as comments and threads. In this way, the proposed scheme detects a local event based on a keyword graph that is constructed through the analysis of the relevant documents. This can improve the accuracy of local event detection by analyzing relevant documents embedded with region-related information using a geographical data dictionary, without requiring users to tag geographic data. In order to verify the superiority of the proposed scheme, we compare it with the existing event detection schemes through various performance evaluations.https://www.mdpi.com/2076-3417/11/2/577social network serviceevent detectionrelevant documentskeyword graph
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Dojin Choi Soobin Park Dongho Ham Hunjin Lim Kyoungsoo Bok Jaesoo Yoo
spellingShingle	Dojin Choi Soobin Park Dongho Ham Hunjin Lim Kyoungsoo Bok Jaesoo Yoo Local Event Detection Scheme by Analyzing Relevant Documents in Social Networks Applied Sciences social network service event detection relevant documents keyword graph
author_facet	Dojin Choi Soobin Park Dongho Ham Hunjin Lim Kyoungsoo Bok Jaesoo Yoo
author_sort	Dojin Choi
title	Local Event Detection Scheme by Analyzing Relevant Documents in Social Networks
title_short	Local Event Detection Scheme by Analyzing Relevant Documents in Social Networks
title_full	Local Event Detection Scheme by Analyzing Relevant Documents in Social Networks
title_fullStr	Local Event Detection Scheme by Analyzing Relevant Documents in Social Networks
title_full_unstemmed	Local Event Detection Scheme by Analyzing Relevant Documents in Social Networks
title_sort	local event detection scheme by analyzing relevant documents in social networks
publisher	MDPI AG
series	Applied Sciences
issn	2076-3417
publishDate	2021-01-01
description	In this paper, we propose a local event detection scheme by analyzing relevant documents in social networks to improve the accuracy of event detection. To detect local events by using geographical data, the proposed scheme embeds them using a geographical data dictionary and generates a weighted keyword graph using social network characteristics. The data left by users in social networks include not only postings but also related documents such as comments and threads. In this way, the proposed scheme detects a local event based on a keyword graph that is constructed through the analysis of the relevant documents. This can improve the accuracy of local event detection by analyzing relevant documents embedded with region-related information using a geographical data dictionary, without requiring users to tag geographic data. In order to verify the superiority of the proposed scheme, we compare it with the existing event detection schemes through various performance evaluations.
topic	social network service event detection relevant documents keyword graph
url	https://www.mdpi.com/2076-3417/11/2/577
work_keys_str_mv	AT dojinchoi localeventdetectionschemebyanalyzingrelevantdocumentsinsocialnetworks AT soobinpark localeventdetectionschemebyanalyzingrelevantdocumentsinsocialnetworks AT donghoham localeventdetectionschemebyanalyzingrelevantdocumentsinsocialnetworks AT hunjinlim localeventdetectionschemebyanalyzingrelevantdocumentsinsocialnetworks AT kyoungsoobok localeventdetectionschemebyanalyzingrelevantdocumentsinsocialnetworks AT jaesooyoo localeventdetectionschemebyanalyzingrelevantdocumentsinsocialnetworks
_version_	1724344206587068416

Local Event Detection Scheme by Analyzing Relevant Documents in Social Networks

Similar Items