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Volume 11
Issue 2
10.3390/app11020577
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Article

Local Event Detection Scheme by Analyzing Relevant Documents in Social Networks

by
Dojin Choi
1,
Soobin Park
1,
Dongho Ham
1,
Hunjin Lim
1,
Kyoungsoo Bok
2 and
Jaesoo Yoo
1,*
1
Department of Information and Communication Engineering, Chungbuk National University, Chungdae-ro 1, Seowon-Gu, Cheongju, Chungbuk 28644, Korea
2
Department of SW Convergence Technology, Wonkwang University, Iksandae 460, Iksan, Jeonbuk 54538, Korea
*
Author to whom correspondence should be addressed.
Appl. Sci. 2021, 11(2), 577; https://doi.org/10.3390/app11020577
Submission received: 16 December 2020 / Revised: 3 January 2021 / Accepted: 6 January 2021 / Published: 8 January 2021
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Abstract

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.
Keywords: social network service; event detection; relevant documents; keyword graph social network service; event detection; relevant documents; keyword graph

Share and Cite

MDPI and ACS Style

Choi, D.; Park, S.; Ham, D.; Lim, H.; Bok, K.; Yoo, J. Local Event Detection Scheme by Analyzing Relevant Documents in Social Networks. Appl. Sci. 2021, 11, 577. https://doi.org/10.3390/app11020577

AMA Style

Choi D, Park S, Ham D, Lim H, Bok K, Yoo J. Local Event Detection Scheme by Analyzing Relevant Documents in Social Networks. Applied Sciences. 2021; 11(2):577. https://doi.org/10.3390/app11020577

Chicago/Turabian Style

Choi, Dojin, Soobin Park, Dongho Ham, Hunjin Lim, Kyoungsoo Bok, and Jaesoo Yoo. 2021. "Local Event Detection Scheme by Analyzing Relevant Documents in Social Networks" Applied Sciences 11, no. 2: 577. https://doi.org/10.3390/app11020577

APA Style

Choi, D., Park, S., Ham, D., Lim, H., Bok, K., & Yoo, J. (2021). Local Event Detection Scheme by Analyzing Relevant Documents in Social Networks. Applied Sciences, 11(2), 577. https://doi.org/10.3390/app11020577

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