Title: A Comparative Study of Machine Learning Algorithms for Predicting Domestic Violence
Vulnerability in Liberian Women
Version: 1 Date: 13 Aug 2023
Reviewer's report:
• The research issue and objectives should be highlighted in a separate paragraph in the
introduction section (second to the last paragraph)
• The authors should summarize the remaining part of the article in the last paragraph.
• Authors should add a new section called “Review of Related Works” and review related works
in a new section, state the gaps discovered from the studies reviewed, and note how their work
improved on the limitations found in the literature.
• The study should be compared with existing systems (state-of-the-art), and authors should state
how it surpassed the existing one and why it performed less or less.
• The authors should discuss the dataset used for the implementation—the attributes and how
the dataset was split (training, validation and testing).
• The limitation of the study should be stated, and they should present future research work.
• Source codes should be provided for replicating the study
• Overall, the English language and presentation style should be improved significantly. There
were a lot of grammatical errors and typos. I suggest you have a colleague proficient in English
and familiar with the subject matter review your manuscript or contact a professional editing
service.
• The authors should include, cite and reference these related 2023 articles
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b. Nie, W., Bao, Y., Zhao, Y., & Liu, A. (2023). Long Dialogue Emotion Detection Based on
Commonsense Knowledge Graph Guidance. IEEE Transactions on Multimedia. doi: 10.1109/
TMM.2023.3267295
c. Guo, F., Zhou, W., Lu, Q., & Zhang, C. (2022). Path extension similarity link prediction
method based on matrix algebra in directed networks. Computer Communications, 187, 83-92.
doi: https://doi.org/10.1016/j.comcom.2022.02.002
d. Wang, S., Hu, X., Sun, J., & Liu, J. (2023). Hyperspectral anomaly detection using ensemble
and robust collaborative representation. Information Sciences, 624, 748-760. doi: https://
doi.org/10.1016/j.ins.2022.12.096
e. Zhou, L., Jin, F., Wu, B., Chen, Z., & Wang, C. L. (2023). Do fake followers mitigate
influencers’ perceived influencing power on social media platforms? The mere number
effect and boundary conditions. Journal of Business Research, 158, 113589. doi: https://
doi.org/10.1016/j.jbusres.2022.113589
f. Lu, S., Liu, M., Yin, L., Yin, Z., Liu, X., Zheng, W.,... Kong, X. (2023). The multi-modal
fusion in visual question answering: a review of attention mechanisms. PeerJ Computer Science,
9, e1400. doi: 10.7717/peerj-cs.1400
g. Liu, X., Shi, T., Zhou, G., Liu, M., Yin, Z., Yin, L.,... Zheng, W. (2023). Emotion
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h. Zheng, W., & Yin, L. (2022). Characterization inference based on joint-optimization of multi-
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cs.908