PONE-D-23-40988Offensive Language Detection in Low Resource Languages: a use case of Persian languagePLOS ONE

Dear Dr. Mnassri,

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PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Partly

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: N/A

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Contribution: compare many models, present new architecture in hope of solving the problem with improved performance and an experiment. Persian Dataset annotation

Relevant literature: adequately cited and discussed w.r.t different languages and different models for the chosen task. However choices are only cursorily supported by literature

Presentation: good

Clarity: fair enough

Organization: fair enough(most revisions relate to organization of paper)

Reproducible results: yes, model seem adaptable

Purpose of model has been well described/ supported by literature

Input/output and internal processing have been fairly described

Illustrations are well made

Reviewer #2: In Iran do not could access Twitter without restrictions and can access Twitter with VPN.

Persian-speaking Twitter users are mostly outside Iran who have migrated for political reasons, and considering that the vast majority of offensive examples are related to political parties and government issues of Iran, offensive words have been used offensive words by these users.

The second group of Twitter users are Iranian authorities who cannot use offensive words in their tweets.

Other people don't have access to Twitter without VPN and it is not a popular network like Instagram in Iran.

Therefore, the sampling used should be Cluster sampling.

What is the reason for not using other machine learning methods in this manuscript?

Reviewer #3: The manuscript's structure is confusing, making it challenging to comprehend the improvements made in comparison to previous studies. The authors should provide a clear description of their enhancements for better understanding.

The manuscript would benefit from the inclusion of a figure to elucidate the proposed method, enhancing the clarity of the methodology.

The structure of the manuscript appears monotonous. Introducing figures and charts would alleviate this issue, making the content more engaging and accessible to readers.

The author references Ensemble Model Results, but there is a lack of explanation. It is crucial to describe what the Ensemble Model is, providing a clear understanding. Additionally, the inclusion of mathematical equations would be beneficial in elucidating the model's workings.

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Reviewer #1: Yes: Sadia Tariq

Reviewer #2: No

Reviewer #3: Yes: Saman Forouzandeh

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Attachments

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Submitted filename: plos one review.docx

Offensive Language Detection in Low Resource Languages: a use case of Persian language

PONE-D-23-40988R1

Dear Dr. Mnassri,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Toqir Rana, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

Reviewer #3: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

Reviewer #3: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

Reviewer #3: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: (No Response)

Reviewer #3: The authors responded to my comments, and from my viewpoint, the manuscript has been accepted.

The authors responded to my comments, and from my viewpoint, the manuscript has been accepted.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

Reviewer #3: No

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