PCSY-D-25-00034

Urban delineation through the lens of commute networks: Leveraging graph embeddings to distinguish socioeconomic groups in cities

PLOS Complex Systems

Dear Dr. Khulbe,

Thank you for submitting your manuscript to PLOS Complex Systems. After careful consideration, we feel that it has merit but does not fully meet PLOS Complex Systems's publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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We look forward to receiving your revised manuscript.

Kind regards,

Hocine Cherifi

Editor-In-Chief

PLOS Complex Systems

Hocine Cherifi

Editor-In-Chief

PLOS Complex Systems

Hocine Cherifi

Editor-in-Chief

PLOS Complex Systems

Journal Requirements:

Additional Editor Comments (if provided):

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Reviewers' Comments:

Reviewer's Responses to Questions

Comments to the Author

1. Does this manuscript meet PLOS Complex Systems’s publication criteria? Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe methodologically and ethically rigorous research with conclusions that are appropriately drawn based on the data presented.

Reviewer #1: No

Reviewer #2: Yes

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

Reviewer #1: N/A

Reviewer #2: Yes

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3. Have the authors made all data underlying the findings in their manuscript fully available (please refer to the Data Availability Statement at the start of the manuscript PDF file)?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception. 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: Yes

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

PLOS Complex Systems 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

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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: Report on the article “Urban delineation through the lens of commute networks: Leveraging graph embeddings to distinguish socioeconomic groups in cities” submitted to publication in PLOS Complex Systems.

In this work, the authors feed commute networks from 12 large cities in the US into GNNs (or NNs or simpler embedding methods) to obtain vectors representing nodes (regions on a city) that can be further clustered. After applying their approach to the data, the authors find that the clusters reflect socioeconomic differences inside the cities.

Despite finding the work interesting and noticing it employs some state-of-the-art machine learning techniques such as Graph Neural Networks, I find it to lack a clear goal in what it intends to accomplish and the data set to be somewhat small. My impression is that it is neither a methodological paper nor a more quaIitative, interpretative work. In addition, the paper could benefit from an English revision as there are several strangely constructed phrases and grammar errors in the main text.

Reviewer #2: This paper proposes the use of Graph Neural Networks (GNNs) for delineating urban communities from census-based commute networks. The authors compare GNN-derived communities to those generated using the COMBO community detection method and assess the resulting clusters through modularity and socioeconomic indicators, particularly median household income.

The paper is clearly written and addresses a timely and relevant topic in urban science and network analysis. However, while the methodology is sound and well-explained, the results do not convincingly demonstrate the advantages of the proposed GNN-based approach over more established community detection methods. This is not my main field, but the paper fails to impress with this novel technique. The novelty and practical impact of the work are therefore limited.

Major Comments:

- The claimed contribution centers on the use of GNNs for urban community detection and the potential computational speed-up. However, the actual benefit of using GNNs over existing community detection methods is unclear. The results (lines 264–268) suggesting better socioeconomic delineation using GNNs are unconvincing—this J-S divergence for socioeconomic factors is not a standard metric for evaluating community partition quality, and even the authors note that the differences are not marked.

- While modularity is used to compare GNN-derived communities with those from COMBO, the paper lacks a broader methodological perspective. Modularity maximization is increasingly seen as outdated. Statistical inference methods based on stochastic block models (e.g., as implemented in graph-tool) offer a more unbiased alternative and should be considered for comparison. Additionally, the black-box nature of GNNs raises concerns about interpretability that are not sufficiently addressed.

- The comparison of socioeconomic differences between community partitions across cities is the most interesting and potentially impactful part of the paper. Figures 3 and Table 3 illustrate this well. However, this section could be discussed more deeply, especially the variation across cities. Figure 4 feels redundant and could be replaced with additional city maps similar to Figure 3 to enrich this analysis.

- The paper claims that GNNs offer a computational advantage. While true in relative terms (e.g., speedups over COMBO), the practical significance is minimal—urban delineation is rarely a task requiring high-speed computation, and the performance gain is unlikely to shift the state of the art.

Minor Comments:

Language issues:

Line 13: “propose of” → “propose using”

Line 43: Please avoid using “it’s” and similar abbreviations.

Literature context:

The "Data Overview" section would benefit from more citations, especially to related work using census, mobility, and socioeconomic data. The field is rich and broader context would improve positioning.

Figure 1:

Consider adding official borough boundaries to make it more interpretable for international readers unfamiliar with U.S. geography.

Method Details:

The GNN and neural network architecture details are adequately described, but given the complexity and relative novelty of GNNs for community detection, more justification of design choices would be helpful, particularly for non-expert readers.

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Reviewer #1: No

Reviewer #2: No

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Urban delineation through the lens of commute networks: Leveraging graph embeddings to distinguish socioeconomic groups in cities

PCSY-D-25-00034R1

Dear Mr. Khulbe,

We are pleased to inform you that your manuscript 'Urban delineation through the lens of commute networks: Leveraging graph embeddings to distinguish socioeconomic groups in cities' has been provisionally accepted for publication in PLOS Complex Systems.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow-up email from a member of our team. 

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they'll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact complexsystems@plos.org.

Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Complex Systems.

Best regards,

Haroldo V. Ribeiro

Academic Editor

PLOS Complex Systems

Hocine Cherifi

Editor-in-Chief

PLOS Complex Systems

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Reviewer Comments (if any, and for reference):

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 #1: All comments have been addressed

Reviewer #2: All comments have been addressed

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2. Does this manuscript meet PLOS Complex Systems's publication criteria? Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe methodologically and ethically rigorous research with conclusions that are appropriately drawn based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available (please refer to the Data Availability Statement at the start of the manuscript PDF file)?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception. 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: Yes

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

PLOS Complex Systems 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

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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 #1: Report on the revised version of the article “Urban delineation through the lens of commute networks: Leveraging graph embeddings to distinguish socioeconomic groups in cities”, submitted for publication in PLOS Complex Systems.

Despite being initially against the publication of this paper, the authors have much improved upon the first version of their manuscript – especially by addressing the comments from the second Reviewer.They have also clarified the study’s objectives and its contribution to the urban-studies literature. Therefore, I am now in favor of its publication.

Reviewer #2: The authors have addressed my comments. I agree that methodologically is nice to see an unsupervised clustering yielding the same results as more classical community detection methods. The manuscript, although it does not show groundbreaking results, is nice to read and can be useful for the community.

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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.

Do you want your identity to be public for this peer review? If you choose “no”, your identity will remain anonymous but your review may still be made public.

For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

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