Integrating contextual sentiment analysis in collaborative recommender systems

Nurul Aida Osman; Shahrul Azman Mohd Noah; Mohammad Darwich; Masnizah Mohd

doi:10.1371/journal.pone.0248695

Peer Review History

Original SubmissionOctober 21, 2020
30 Nov 2020 Decision Letter - M. Usman Ashraf, Editor PONE-D-20-33161 Integrating contextual sentiment analysis in collaborative recommender systems PLOS ONE Dear Dr. Noah, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’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. Please submit your revised manuscript by Jan 09 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. 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Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols We look forward to receiving your revised manuscript. Kind regards, M. Usman Ashraf, Ph.D Academic Editor PLOS ONE Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. Thank you for stating in your Funding Statement: "This research is partially supported by the Malaysia Ministry of Education Grant FRGS/1/2014/ICT02/UKM/01/1 awarded to Shahrul Azman Mohd Noah. The funder did not play any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript." Please provide an amended statement that declares all the funding or sources of support (whether external or internal to your organization) received during this study, as detailed online in our guide for authors at http://journals.plos.org/plosone/s/submit-now. Please also include the statement “There was no additional external funding received for this study.” in your updated Funding Statement. Please include your amended Funding Statement within your cover letter. We will change the online submission form on your behalf. 3. Thank you for submitting the above manuscript to PLOS ONE. During our internal evaluation of the manuscript, we found some occurrences of overlapping text with the following previous publication(s), some of which you are an author, which needs to be addressed: - https://ieeexplore.ieee.org/document/8464694 - https://ieeexplore.ieee.org/document/7797377 - https://medium.com/@m_n_malaeb/recall-and-precision-at-k-for-recommender-systems-618483226c54 - https://www.toptal.com/deep-learning/4-sentiment-analysis-accuracy-traps - https://www.rroij.com/open-access/real-time-sentiment-classification-usingunsupervised-reviews.php?aid=48846&view=mobile - https://link.springer.com/book/10.1007%2F978-3-319-29659-3 We would like to make you aware that copying extracts from previous publications word-for-word, particularly outside the methods section, is unacceptable. In addition, the reproduction of text from published reports has implications for the copyright that may apply to the publications. Please revise the manuscript to quote or rephrase the duplicated text and cite your sources for text outside the methods section. Please note that further consideration is dependent on the submission of a manuscript that addresses these concerns about the overlap in text with published work. [Note: HTML markup is below. Please do not edit.] 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: Partly ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes ****** 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: Yes ****** 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 ****** 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: Discuss Problem Statement clearly in manuscript, discuss more state-of-the-art work, Explain perfjoamcne metrics very clearly and justify, why you used the mentioned performance metrics in the manuscript, need to add more resulting graphs. add a new section named as Future Work, and discuss future work. Reviewer #2: This paper describes a recommendation system approach that leverages sentiment analysis to improve performance. The following issues should be addressed before this paper can be considered for publication: -Table 1 could be replaced by a Figures with more values of distinct lambda. - It is not clear if your results are significant better than other competing approaches. - A better context on recommendation systems should be provided. For example, it is not used only for products. It can be used in wider contexts. See and mention e.g. applications in collaboration and citation analysis doi: 10.1209/0295-5075/99/48002 doi:10.1007/s00799-020-00288-2 - Figure quality should be much improved. - there is no need to define cosine similarity. - It would interesting to mention that other strategies for recommendation system could also benefit from the proposed strategy. For example, graph based approaches could benefit from the proposed sentiment analysis in recommendation systems. See and mention e.g. doi: 10.1016/J.INS.2018.02.047 doi: 10.1145/544220.544231 for strategies that could be combined and benefit from your approach. - TAbles (in figure) should be provided in a standard (e.g. latex) way, and not in a microsoft office figure. - Perspectives for future works should be provided. Which other works or lines of research could benefit from this strategy? ****** 6. 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 #1: Yes:** Dr. Mudassar Ahmad. Reviewer #2: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0248695.r001
Revision 1
18 Feb 2021 Author Response Editorial's comments 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at: https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf >>> Revised accordingly 2. Thank you for stating in your Funding Statement: "This research is partially supported by the Malaysia Ministry of Education Grant FRGS/1/2014/ICT02/UKM/01/1 awarded to Shahrul Azman Mohd Noah. The funder did not play any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript." Please provide an amended statement that declares all the funding or sources of support (whether external or internal to your organization) received during this study, as detailed online in our guide for authors at http://journals.plos.org/plosone/s/submit-now. Please also include the statement “There was no additional external funding received for this study.” in your updated Funding Statement. Please include your amended Funding Statement within your cover letter. We will change the online submission form on your behalf. >>> The funding statement has been revised and updated 3. Thank you for submitting the above manuscript to PLOS ONE. During our internal evaluation of the manuscript, we found some occurrences of overlapping text with the following previous publication(s), some of which you are an author, which needs to be addressed: - https://ieeexplore.ieee.org/document/8464694 - https://ieeexplore.ieee.org/document/7797377 - https://medium.com/@m_n_malaeb/recall-and-precision-at-k-for-recommender-systems-618483226c54 - https://www.toptal.com/deep-learning/4-sentiment-analysis-accuracy-traps - https://www.rroij.com/open-access/real-time-sentiment-classification-usingunsupervised-reviews.php?aid=48846&view=mobile - https://link.springer.com/book/10.1007%2F978-3-319-29659-3 We would like to make you aware that copying extracts from previous publications word-for-word, particularly outside the methods section, is unacceptable. In addition, the reproduction of text from published reports has implications for the copyright that may apply to the publications. Please revise the manuscript to quote or rephrase the duplicated text and cite your sources for text outside the methods section. Please note that further consideration is dependent on the submission of a manuscript that addresses these concerns about the overlap in text with published work. >>> Citation added and sentences been rephrased 4. Review Comments to the Author Reviewer #1: a) Discuss Problem Statement clearly in manuscript, discuss more state-of-the-art work, b) Explain performance metrics very clearly and justify, why you used the mentioned performance metrics in the manuscript, need to add more resulting graphs. c) Add a new section named as Future Work, and discuss future work. >>> Responses to Reviewer #1: a. Problem statement and state-of-the-art work were further elaborated in the Introduction section. b. Explanation of the used performance metrics were further elaborated and subsequently justified in the Experiments and Results section. c. A new section named Future Work is included in the revised version of the paper Reviewer #2: This paper describes a recommendation system approach that leverages sentiment analysis to improve performance. The following issues should be addressed before this paper can be considered for publication: a) Table 1 could be replaced by a Figures with more values of distinct lambda. b) It is not clear if your results are significant better than other competing approaches. c) A better context on recommendation systems should be provided. For example, it is not used only for products. It can be used in wider contexts See and mention e.g. applications in collaboration and citation analysis doi: 10.1209/0295-5075/99/48002 doi:10.1007/s00799-020-00288-2 d) Figure quality should be much improved. e) There is no need to define cosine similarity. f) It would interesting to mention that other strategies for recommendation system could also benefit from the proposed strategy. For example, graph based approaches could benefit from the proposed sentiment analysis in recommendation systems. See and mention e.g. doi: 10.1016/J.INS.2018.02.047 doi: 10.1145/544220.544231 for strategies that could be combined and benefit from your approach. g) TAbles (in figure) should be provided in a standard (e.g. latex) way, and not in a microsoft office figure. h) Perspectives for future works should be provided. Which other works or lines of research could benefit from this strategy? >>> Responses to Reviewer #2: a) Noted. Table 1 has been replaces by a figures with more values of distinct lambda ranging from 0.2 till 0.8 to indicate more clear and specific results. b) Results of significant test were included in Table 5 and 6. The results are significant better that the other two baselines which is traditional recommender system and traditional sentiment based recommender system. It has been proven in the experiments by comparing the results using the same format, same domain and same number of test sets. c) In this experiment, we demonstrated in a wider context not only focus in one domain. We also use for movie and films domain not only for products. Hence, it can be used in different applications as well by performing in other domain such as medicine and political domains (See Future Works section). d) The quality of figures have been improved. e) The definition of Cosine similarity definition has been removed. f) Other strategies that can be benefit from the proposed approach as recommended by the 2nd reviewer is included in the Discussion & Conclusion section. g) Tables (in figures) has been changed in latex format. h) Prospective for future work has been added in the Future Work section. Attachments Attachment Submitted filename: 1st decision-Response to Reviewers Comments (2).docx https://doi.org/10.1371/journal.pone.0248695.r002
4 Mar 2021 Decision Letter - M. Usman Ashraf, Editor Integrating contextual sentiment analysis in collaborative recommender systems PONE-D-20-33161R1 Dear Dr. Noah, 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. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. 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 onepress@plos.org. Kind regards, M. Usman Ashraf, Ph.D Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0248695.r003
Formally Accepted
12 Mar 2021 Acceptance Letter - M. Usman Ashraf, Editor PONE-D-20-33161R1 Integrating contextual sentiment analysis in collaborative recommender systems Dear Dr. Noah: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. M. Usman Ashraf Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0248695.r004

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