@article{ART003130987},
author={Jin-Gyeong Kim and Eun-Young Park and Da–Sol Kim and Cho-Won Kim and Jiyeon Kim},
title={Development of a Model for Identifying Drug Organizations and Their Scale through Tweet Clustering},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2024},
volume={29},
number={10},
pages={207-218}
TY - JOUR
AU - Jin-Gyeong Kim
AU - Eun-Young Park
AU - Da–Sol Kim
AU - Cho-Won Kim
AU - Jiyeon Kim
TI - Development of a Model for Identifying Drug Organizations and Their Scale through Tweet Clustering
JO - Journal of The Korea Society of Computer and Information
PY - 2024
VL - 29
IS - 10
PB - The Korean Society Of Computer And Information
SP - 207
EP - 218
SN - 1598-849X
AB - In this paper, we propose a model for identifying drug trafficking organizations and assessing their scale by collecting drug promotional tweets from the social media platform ‘X,’ with a focus on investigating drug crimes that frequently occur among teenagers and young adults. Recently, various cyber crimes, such as drug distribution, illegal gambling, and sex offense, have been on the rise, exploiting the anonymity provided by social media. Drug trafficking organizations, in particular, operate in a decentralized cell structure, where each member receives anonymous instructions regarding only their specific role and is not directly connected to other members. To track these types of crimes, we designed experimental scenarios using various clustering algorithms, such as K-means Clustering and Spectral Clustering, alongside text embedding models like BERT (Bidirectional Encoder Representations from Transformers) and GloVe (Global Vectors for Word Representation).
Furthermore, the clustering results derived from each scenario are validated using Jaccard Similarity and a full-scale investigation. We then analyze tweet clusters identified as the same drug organization across all scenarios, prioritizing the identification of high-priority accounts for cyber investigations.
KW - Cyber Investigation;Drug;Social Media;Tweet;Clustering
DO -
UR -
ER -
Jin-Gyeong Kim, Eun-Young Park, Da–Sol Kim, Cho-Won Kim and Jiyeon Kim. (2024). Development of a Model for Identifying Drug Organizations and Their Scale through Tweet Clustering. Journal of The Korea Society of Computer and Information, 29(10), 207-218.
Jin-Gyeong Kim, Eun-Young Park, Da–Sol Kim, Cho-Won Kim and Jiyeon Kim. 2024, "Development of a Model for Identifying Drug Organizations and Their Scale through Tweet Clustering", Journal of The Korea Society of Computer and Information, vol.29, no.10 pp.207-218.
Jin-Gyeong Kim, Eun-Young Park, Da–Sol Kim, Cho-Won Kim, Jiyeon Kim "Development of a Model for Identifying Drug Organizations and Their Scale through Tweet Clustering" Journal of The Korea Society of Computer and Information 29.10 pp.207-218 (2024) : 207.
Jin-Gyeong Kim, Eun-Young Park, Da–Sol Kim, Cho-Won Kim, Jiyeon Kim. Development of a Model for Identifying Drug Organizations and Their Scale through Tweet Clustering. 2024; 29(10), 207-218.
Jin-Gyeong Kim, Eun-Young Park, Da–Sol Kim, Cho-Won Kim and Jiyeon Kim. "Development of a Model for Identifying Drug Organizations and Their Scale through Tweet Clustering" Journal of The Korea Society of Computer and Information 29, no.10 (2024) : 207-218.
Jin-Gyeong Kim; Eun-Young Park; Da–Sol Kim; Cho-Won Kim; Jiyeon Kim. Development of a Model for Identifying Drug Organizations and Their Scale through Tweet Clustering. Journal of The Korea Society of Computer and Information, 29(10), 207-218.
Jin-Gyeong Kim; Eun-Young Park; Da–Sol Kim; Cho-Won Kim; Jiyeon Kim. Development of a Model for Identifying Drug Organizations and Their Scale through Tweet Clustering. Journal of The Korea Society of Computer and Information. 2024; 29(10) 207-218.
Jin-Gyeong Kim, Eun-Young Park, Da–Sol Kim, Cho-Won Kim, Jiyeon Kim. Development of a Model for Identifying Drug Organizations and Their Scale through Tweet Clustering. 2024; 29(10), 207-218.
Jin-Gyeong Kim, Eun-Young Park, Da–Sol Kim, Cho-Won Kim and Jiyeon Kim. "Development of a Model for Identifying Drug Organizations and Their Scale through Tweet Clustering" Journal of The Korea Society of Computer and Information 29, no.10 (2024) : 207-218.
