TY - GEN
T1 - Lawyering Social
T2 - 5th International Conference on Informatics and Computational Sciences, ICICos 2021
AU - Meilani, Zahra Dyah
AU - Nizar, Ivan Muhammad
AU - Sunandar, Muhamad Fikri
AU - Hidayati, Shintami Chusnul
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Along with the increasing use of online communication during the current Covid-19 pandemic, people have become more active in the social media platforms like Facebook and Twitter, whether it be through by posting their content online or by reading the posts of others. Undoubtedly, it has a negative impact in the form of cybercrimes, especially when public understanding of cyber law is still low. To address this issue, we propose an approach to identifying cybercrime on social media posts, with case studies on Indonesian cybercrime law. The main challenge in solving the problem is the use of informal language and non-standard writing. Therefore, we exploit the informative value of terms in that post by paying attention to standard patterns in Indonesian grammar and writing structure with a classifier based on the voting ensemble learning model. The experimental results show that the proposed approach significantly outperformed baselines, with an accuracy of more than 90%. Thus, it proves the effectiveness of the approach in generalizing the content of social media posts according to the category of cybercrime law.
AB - Along with the increasing use of online communication during the current Covid-19 pandemic, people have become more active in the social media platforms like Facebook and Twitter, whether it be through by posting their content online or by reading the posts of others. Undoubtedly, it has a negative impact in the form of cybercrimes, especially when public understanding of cyber law is still low. To address this issue, we propose an approach to identifying cybercrime on social media posts, with case studies on Indonesian cybercrime law. The main challenge in solving the problem is the use of informal language and non-standard writing. Therefore, we exploit the informative value of terms in that post by paying attention to standard patterns in Indonesian grammar and writing structure with a classifier based on the voting ensemble learning model. The experimental results show that the proposed approach significantly outperformed baselines, with an accuracy of more than 90%. Thus, it proves the effectiveness of the approach in generalizing the content of social media posts according to the category of cybercrime law.
KW - Indonesian cyber law
KW - UU ITE
KW - cybercrime
KW - social media post
KW - text mining
UR - http://www.scopus.com/inward/record.url?scp=85142429133&partnerID=8YFLogxK
U2 - 10.1109/ICICoS53627.2021.9651801
DO - 10.1109/ICICoS53627.2021.9651801
M3 - Conference contribution
AN - SCOPUS:85142429133
T3 - Proceedings - International Conference on Informatics and Computational Sciences
SP - 266
EP - 271
BT - Proceeding - 5th International Conference on Informatics and Computational Sciences, ICICos 2021
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 24 November 2021 through 25 November 2021
ER -