Crime-Intent Sentiment Detection on Twitter Data Using Machine Learning

Biodoumoye George Bokolo; Ebikela Ogegbene-Ise; Lei Chen; Qingzhong Liu

doi:10.1109/CACRE58689.2023.10208384

Crime-Intent Sentiment Detection on Twitter Data Using Machine Learning

Biodoumoye George Bokolo, Ebikela Ogegbene-Ise, Lei Chen, Qingzhong Liu

Information Technology

Research output: Contribution to book or proceeding › Conference article › peer-review

4 Scopus citations

Abstract

This research examines sentiment analysis in the context of crime intent using machine learning algorithms. A comparison is made between a crime intent dataset generated from a Twitter developer account and Kaggle's sentiment140 dataset for Twitter sentiment analysis. The algorithms employed include Support Vector Machine (SVM), Naïve Bayes, and Long Short-Term Memory (LSTM). The findings indicate that LSTM outperforms the other algorithms, achieving high accuracy (97%) and precision (99%) in detecting crime tweets. Thus, it is concluded that the crime tweets were accurately identified.

Original language	English
Title of host publication	Proceedings - 2023 8th International Conference on Automation, Control and Robotics Engineering, CACRE 2023
Editors	Fumin Zhang, Lichuan Zhang
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	79-83
Number of pages	5
ISBN (Electronic)	9798350302776
ISBN (Print)	9798350302776
DOIs	https://doi.org/10.1109/CACRE58689.2023.10208384
State	Published - Jul 1 2023
Event	8th International Conference on Automation, Control and Robotics Engineering, CACRE 2023 - Hong Kong, China Duration: Jul 13 2023 → Jul 15 2023

Publication series

Name	2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)

Conference

Conference	8th International Conference on Automation, Control and Robotics Engineering, CACRE 2023
Country/Territory	China
City	Hong Kong
Period	07/13/23 → 07/15/23

Scopus Subject Areas

Artificial Intelligence
Computer Vision and Pattern Recognition
Hardware and Architecture
Aerospace Engineering
Control and Systems Engineering
Mechanical Engineering
Safety, Risk, Reliability and Quality
Control and Optimization

Keywords

LSTM
Naïve Bayes
SVM
crime-intent
criminal
cyberbullying
sentiment analysis

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/CACRE58689.2023.10208384

Cite this

Bokolo, B. G., Ogegbene-Ise, E., Chen, L., & Liu, Q. (2023). Crime-Intent Sentiment Detection on Twitter Data Using Machine Learning. In F. Zhang, & L. Zhang (Eds.), Proceedings - 2023 8th International Conference on Automation, Control and Robotics Engineering, CACRE 2023 (pp. 79-83). (2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CACRE58689.2023.10208384

Bokolo, Biodoumoye George ; Ogegbene-Ise, Ebikela ; Chen, Lei et al. / Crime-Intent Sentiment Detection on Twitter Data Using Machine Learning. Proceedings - 2023 8th International Conference on Automation, Control and Robotics Engineering, CACRE 2023. editor / Fumin Zhang ; Lichuan Zhang. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 79-83 (2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)).

@inproceedings{36f4b5c78ae34e26a741378430c04993,

title = "Crime-Intent Sentiment Detection on Twitter Data Using Machine Learning",

abstract = "This research examines sentiment analysis in the context of crime intent using machine learning algorithms. A comparison is made between a crime intent dataset generated from a Twitter developer account and Kaggle's sentiment140 dataset for Twitter sentiment analysis. The algorithms employed include Support Vector Machine (SVM), Na{\"i}ve Bayes, and Long Short-Term Memory (LSTM). The findings indicate that LSTM outperforms the other algorithms, achieving high accuracy (97\%) and precision (99\%) in detecting crime tweets. Thus, it is concluded that the crime tweets were accurately identified.",

keywords = "LSTM, Na{\"i}ve Bayes, SVM, crime-intent, criminal, cyberbullying, sentiment analysis",

author = "Bokolo, \{Biodoumoye George\} and Ebikela Ogegbene-Ise and Lei Chen and Qingzhong Liu",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 8th International Conference on Automation, Control and Robotics Engineering, CACRE 2023 ; Conference date: 13-07-2023 Through 15-07-2023",

year = "2023",

month = jul,

day = "1",

doi = "10.1109/CACRE58689.2023.10208384",

language = "English",

isbn = "9798350302776",

series = "2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "79--83",

editor = "Fumin Zhang and Lichuan Zhang",

booktitle = "Proceedings - 2023 8th International Conference on Automation, Control and Robotics Engineering, CACRE 2023",

address = "United States",

}

Bokolo, BG, Ogegbene-Ise, E, Chen, L & Liu, Q 2023, Crime-Intent Sentiment Detection on Twitter Data Using Machine Learning. in F Zhang & L Zhang (eds), Proceedings - 2023 8th International Conference on Automation, Control and Robotics Engineering, CACRE 2023. 2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE), Institute of Electrical and Electronics Engineers Inc., pp. 79-83, 8th International Conference on Automation, Control and Robotics Engineering, CACRE 2023, Hong Kong, China, 07/13/23. https://doi.org/10.1109/CACRE58689.2023.10208384

Crime-Intent Sentiment Detection on Twitter Data Using Machine Learning. / Bokolo, Biodoumoye George; Ogegbene-Ise, Ebikela; Chen, Lei et al.
Proceedings - 2023 8th International Conference on Automation, Control and Robotics Engineering, CACRE 2023. ed. / Fumin Zhang; Lichuan Zhang. Institute of Electrical and Electronics Engineers Inc., 2023. p. 79-83 (2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)).

Research output: Contribution to book or proceeding › Conference article › peer-review

TY - GEN

T1 - Crime-Intent Sentiment Detection on Twitter Data Using Machine Learning

AU - Bokolo, Biodoumoye George

AU - Ogegbene-Ise, Ebikela

AU - Chen, Lei

AU - Liu, Qingzhong

PY - 2023/7/1

Y1 - 2023/7/1

N2 - This research examines sentiment analysis in the context of crime intent using machine learning algorithms. A comparison is made between a crime intent dataset generated from a Twitter developer account and Kaggle's sentiment140 dataset for Twitter sentiment analysis. The algorithms employed include Support Vector Machine (SVM), Naïve Bayes, and Long Short-Term Memory (LSTM). The findings indicate that LSTM outperforms the other algorithms, achieving high accuracy (97%) and precision (99%) in detecting crime tweets. Thus, it is concluded that the crime tweets were accurately identified.

AB - This research examines sentiment analysis in the context of crime intent using machine learning algorithms. A comparison is made between a crime intent dataset generated from a Twitter developer account and Kaggle's sentiment140 dataset for Twitter sentiment analysis. The algorithms employed include Support Vector Machine (SVM), Naïve Bayes, and Long Short-Term Memory (LSTM). The findings indicate that LSTM outperforms the other algorithms, achieving high accuracy (97%) and precision (99%) in detecting crime tweets. Thus, it is concluded that the crime tweets were accurately identified.

KW - LSTM

KW - Naïve Bayes

KW - SVM

KW - crime-intent

KW - criminal

KW - cyberbullying

KW - sentiment analysis

UR - https://www.scopus.com/pages/publications/85169420173

U2 - 10.1109/CACRE58689.2023.10208384

DO - 10.1109/CACRE58689.2023.10208384

M3 - Conference article

AN - SCOPUS:85169420173

SN - 9798350302776

T3 - 2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)

SP - 79

EP - 83

BT - Proceedings - 2023 8th International Conference on Automation, Control and Robotics Engineering, CACRE 2023

A2 - Zhang, Fumin

A2 - Zhang, Lichuan

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 8th International Conference on Automation, Control and Robotics Engineering, CACRE 2023

Y2 - 13 July 2023 through 15 July 2023

ER -

Bokolo BG, Ogegbene-Ise E, Chen L, Liu Q. Crime-Intent Sentiment Detection on Twitter Data Using Machine Learning. In Zhang F, Zhang L, editors, Proceedings - 2023 8th International Conference on Automation, Control and Robotics Engineering, CACRE 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 79-83. (2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)). doi: 10.1109/CACRE58689.2023.10208384

Crime-Intent Sentiment Detection on Twitter Data Using Machine Learning

Abstract

Publication series

Conference

Scopus Subject Areas

Keywords

UN SDGs

Access to Document

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