Identifying Emerging Issues in the Seafood Industry Based on a Text Mining Approach

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The presented paper is devoted to Identifying Emerging Issues for (maybe it could be “in”?) the Seafood Industry. The authors generate relevant time series to capture the evolution of keyword occurrences, unveiling dynamic patterns. While a formal analysis is applied in a reasonably suitable form, it requires improvement.

1.       DWT is a critical aspect of the research, but its presentation lacks clarity and depth, lacking both formal and intuitive explanations.

2.       The section titled "Decision for Emerging Issues Candidates" needs significant expansion and revision as it currently summarizes the computational process, which is central to the research. The authors seem to formally understand the mathematical tools applied, but this needs more elucidation.

3.       It's unclear why the K-means algorithm is preferred over K-medoids, especially considering the small cluster sizes. Additionally, the method for choosing the number of clusters is not explained.

4.       The clustering results are validated through the behavior of the S-curves in the clusters. However, since clustering is based on DWT distances, it appears that the S-curves would naturally behave similarly.

5.       The experimental section is overwhelming. While the authors may aim to impress the reader, the current form is confusing and challenging to comprehend. The conclusion is also challenging to follow after such an extensive section, making it difficult to discern the main conclusions and the paper's contribution.

Comments on the Quality of English Language

Minor editing of English language required

Author Response

We would like to thank the Referee for the thoughtful comments on our manuscript. We will provide detailed responses to each of the reviewer’s comments.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The authors have developed a logistic growth model to explore critical and emerging issues within the seafood industry. To enhance the manuscript's suitability for publication, the authors need to address several key points:

The significance, novelty, and appeal of the chosen topic to the readership are not clearly articulated in the manuscript. It is essential to elucidate why this subject matter is relevant and engaging for the audience.

A more comprehensive justification for employing Dynamic Time Warping (DTW) as the method for trend analysis is necessary. The rationale behind choosing DTW over alternative methodologies should be clarified, along with references to previous studies that have utilized DTW for similar analyses.

Figure 9 currently appears to be invisible, giving the impression that the data is missing. This issue needs rectification to ensure the figure is visible and informative to the reader.

The use of a word cloud in its current form does not effectively convey information, as many words are indiscernible. It is recommended to incorporate a term frequency-inverse document frequency (tf-idf) approach, presented in a tabular format, to highlight the most prominent words relevant to the study. This approach would provide a clearer and more quantifiable insight into the key terms associated with the task.

It would be beneficial to mention that alternative text analysis methods could offer varied perspectives in identifying emerging issues. Examples of such approaches include:
'Revealing the semantic and emotional structure of suicide notes with
cognitive network science', 'Using virtual edges to improve the
discriminability of co-occurrence text networks', and '
Full‐text citation analysis: A new method to enhance scholarly networks'
The methodology employed by the authors to extract keywords is not explicitly detailed in the manuscript. the authors should clearly describe the keyword extraction process within the text.
Comments on the Quality of English Language

Moderate modifications are required.

Author Response

We would like to thank the Referee for the thoughtful comments on our manuscript. We will provide detailed responses to each of the reviewer’s comments.

Author Response File: Author Response.pdf