PONE-D-21-32417Difficulty and pleasure in the comprehension of verb-based metaphor sentences: a behavioral studyPLOS ONE

Dear Dr. Errington,

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. As you'll see, the reviewers are quite positive about this study.  And I agree. Your paper is very well-written, the methodology is sound, and the results are potentially interesting. At the same time, the reviewers raised several issues that need to be addressed in a revision. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Below I summarize some of the main concerns which would need to be addressed.  In addition, each of the reviewers' specific comments needs be addressed (or an explanation provided for not doing so).

First, the logic underlying the use of your individual difference variable (SST) needs to be clarified (see Reviewer 1), as well as the appropriateness of your analyses for examining its role (see Reviewer 2).

Second, as noted by Reviewer 1, there is a substantial literature on the relationship between aesthetic preferences and processing fluency/difficulty that is not referenced in your paper. You should include some of this literature in your revision; doing so may help you clarify the meaning of your results.

Third, some of the analyses you report may be less than optimal for the issues you are investigating (see especially Reviewer 2). As noted by Reviewer 2, examining the ease-pleasure relationship separately for the different categories may result in the hypothesized curvilinear relationship being obscured.  Why not examine the ease-pleasure relationship across the entire data set? As well, there appears to be some redundancy in some of the models you test because you simultaneously include comprehension ease as well as metaphor category (which is based, in part, on comprehension ease).

Fourth, you should describe how your sample size was determined and address the issue of power to detect your predicted effects.

Fifth, participants in your experiment provided four ratings.  However, the analyses you report include only two (pleasure and ease).  I assume you’ve undertaken analyses with the other two rating scales (imageability and emotion) and some mention should be made of them (at the very least in a footnote).

Please submit your revised manuscript by Jan 03 2022 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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If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

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We look forward to receiving your revised manuscript.

Kind regards,

Thomas Holtgraves, Ph.D.

Academic Editor

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: Partly

Reviewer #2: Partly

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

Reviewer #1: Yes

Reviewer #2: No

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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: 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

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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: 1. It is difficult to determine what kind of “pleasure” the authors are trying to address. The terminology varies: striking, thrilling, affective, pleasurable, etc. There is a substantial psychometric issue lurking here that should be addressed more directly. The authors may find it useful to locate “effective, satisfying, or powerful” (the wording eventually chosen for their ratings; pp. 18-19) within the most comprehensive available survey of aesthetic “emotions” (Schindler et al. 2017). Although the author’s formalist intent is explicit (“how much you liked the way the message was expressed”; l. 434), the kind of “affectiveness” that is at stake also remains obscure.

Schindler, I., Hosoya, G., Menninghaus, W., Beermann, U., Wagner, V., Eid, M., & Scherer, K. R. (2017). Measuring aesthetic emotions: A review of the literature and a new assessment tool. PLOS ONE, 12(6), e0178899. https://doi.org/10.1371/journal.pone.017889

2. The authors indicate that their research is “informed” by Giora’s “optimal innovation hypothesis” (see especially, Giora et al. 2017).

a. One issue in Giora’s work is how to differentiate default literal, default metaphoric, and non-default metaphoric sentences so that metaphoric default salience can be assessed independently of metaphoric non-default salience. It is somewhat disconcerting, then, to learn that the authors did not include the default literal sentences in Study 1 because “we were only interested in metaphor comprehension” (l. 368). Giora is primarily interested in metaphor comprehension, too; so, the reason for ignoring differences between default literal and default metaphoric sentences should be more clearly articulated—and in terms she would understand.

b. A related but separate issue is how to differentiate metaphoric sentences so that, independently of defaultness, metaphoric vehicles can be contrasted according to the extent to which they are “domain-specific” (l. 167). The authors hypothesize that excessive domain specificity may make a metaphor too difficult to be pleasurable. However, emphasizing domain-specificity may oversimplify the problem. For example, Katz and Al-Azary (2017) differentiate (a) the distance between the domain of the topic and the domain of the vehicle; (b) the semantic density of the topic and of the vehicle; and (c) the specificity of the topic or vehicle within their respective domains (“domain-specificity”?). The authors should be encouraged to compare the Katz and Al-Zahry framework with their own. For example, perhaps they can clarify whether their use of word2vec (l. 267) converges with the Katz and Al-Zahry version of computational semantics.

Katz, A. N., & Al-Azary, H. (2017). Principles that promote bidirectionality in verbal metaphor. Poetics Today, 38(1), 35–59. https://doi.org/10.1215/03335372-3716215

c. Contextualizing their hypothesis within the Katz and Alzary (2017) framework may also enable the authors to clarify their rationale for including the Semantic Similarities Test (SST) as an individual differences measure of “the ability to identify conceptual mappings between words” (l. 181). The SST assesses “crystalized verbal intelligence” by evaluating a person’s ability to find similarities between two concepts. Was this measure expected to reflect (a) the capacity to identify similarities between vehicle and topic concepts even when they are “domain-specific”; (b) the capacity to identify similarities between vehicle and topic concepts even when they are from distant domains; or (c) the capacity to identify similarities between vehicle and topic concepts because they are (especially for some individuals) semantically dense? As it stands, the SST is not conceptually well coordinated with the author’s research paradigm.

d. It is a bit unsettling that there is no reference to other literature indicating that aesthetic preferences are determined by processing fluency/difficulty (cf. Reber et al., 2004), including the tradition of proposed curvilinear relations between object complexity and interest/pleasure (e.g., Berlyne, 1971). Research in the latter tradition substantiates how difficult it is to assess curvilinear relations beccause the direction of the relationship differs at different levels of the variables. More to the point, it is not clear where to locate “optimal” and “excessive” metaphors on the hypothesized curvilinear relation with pleasure. That difficulty should at least be mentioned.

3. Perhaps the most innovative aspect of the authors’ design is their attempt to examine novel extensions of familiar metaphors. In this reviewer’s judgment, their procedures for doing so are promising. The procedures used to develop these extended metaphors led to at least two interesting results. First, optimal extensions and excessive extensions were rated as the “most figurative” (l. 358). Second, metaphor extensions were rated as more pleasurable than verb variants, indicating that “innovations that increase … richness can increase pleasure without decreasing difficulty. These results are worth building on in future research efforts.

a. To explain these results, the authors emphasize “textual and situational context.” However, it may be more promising to examine specifically extended metaphors. The authors offer the following hypothesis: “The figurative meaning of the familiar metaphor is likely to be already active when the reader reaches the extension, which can more easily create the pleasurable tension between default and non-default interpretations.” The possibility of examining the interplay (and tension) between a familiar metaphor and a subsequent extension is within these authors’ methodological reach.

b. As their project unfolds, the authors may want to take advantage of Sullivan’s (2019) recent examination of mixed metaphors, some of which are subject to the domain specificity problem that makes them anathema in scholarly circles—but perhaps of particular interest to the authors.

Sullivan, K. (2018). Mixed metaphors: Their use and abuse. Bloomsbury Publishing.

4. A not-so-important note (l. 290): a 7-point rating scale is not a “Likert scale.” This common misuse of that phrase should not be repeated here.

Reviewer #2: In this paper, the authors examine the “optimal innovation hypothesis”, which posits that language is most enjoyable when it evokes a non-default response, but also brings to mind the default response so that the two responses can be weighted against one another. The authors examined this hypothesis by carefully constructing a stimulus set of metaphors and obtaining subjective ratings of pleasurability for these metaphors.

First, the paper was well-written. It discussed an interesting theory within figurative language research. Also, I really enjoyed the writing style. I thought the examples used were interesting and made the paper exciting, and the authors also explained the theories and hypotheses clearly.

Second, I think the stimuli for this study are very nice, and I appreciate that the authors made them available on OSF. The authors carefully considered a variety of factors, including semantic distance measures and frequency. I also totally agree with the authors that there is an overemphasis on examining nominal metaphors, and I appreciate that they developed a set of verb metaphors and metaphor extensions and made these publicly available. I was very impressed by this aspect of the study.

That being said, I have major concern with the analyses the authors conducted to examine their hypotheses (Section 3.2: Results and Discussion). I question the logic of these analyses for a couple reasons. First of all, the authors mention that there was no U-shaped curve observed in the data. However, to examine this, they split the familiar, optimal, and excessive metaphors into separate categories and examined these curves separately (Supplementary Figure). I think this defeats the purpose as this restricts the range of the data in each case. The whole point of the optimal and excessive categories was that they were supposed to increase difficulty, so it doesn’t make sense to me why difficulty would be examined within each of these categories separately. Wouldn’t it make more sense to either 1) look at the relationship between ease and pleasure collapsed across all the metaphors, or 2) compare the means between the categories directly (metaphors in the optimal category should have significantly higher pleasurability ratings than the familiar and excessive categories)? This criticism carries through to the first lme model (Model 1). Both the categories and the continuous ratings of ease were included in the model, but aren’t these essentially the same variable? Therefore, (if I understand lme correctly) if there is a significant effect of a category, this effect is independent of ease since ease is a variable in the model. However, the categories were specifically constructed to vary in ease, so the critical variable in the category is being controlled out of the category. Also, I didn’t quite get the logic of Model 2. It considered individual differences, but the relative differences of ease between the metaphors should still be preserved regardless of individual differences in figurative comprehension, so I’m also not sure how that tests the hypothesis.

In the discussion, the authors state “the optimal metaphor extensions were rated as intermediate in terms of ease of comprehension, but highest in terms of pleasure”. And also, “familiar metaphors were rated both easier and more pleasurable than ‘optimal’ verb variants, which were rated both easier and more pleasurable than ‘excessive’ verb variants”. But these comparisons were not tested statistically, and weren’t really discussed much in the Results. I think the lme models obscure these findings, which are probably the most interesting part of the data.

I think this is a fixable problem though. I would recommend just conducting some standard statistics on the data, namely, an ANOVA between the categories (not considering ease ratings) and a correlation between ease and pleasurability (independent of the categories). It might be beneficial to run some separate ANOVAs to compare both optimal vs. excessive, but also verb vs. extension, since there seemed to be a trend in extensions being more pleasurable. I think this would more directly test your hypotheses and would make the Results section better fit with the Discussion section.

As one additional small point, I didn’t understand the NGram frequency graph on page 14. I think the axes need to be labelled or else the graph needs to be better explained in the caption.

Overall, I think this paper has a lot of potential. The stimuli were very carefully constructed, and the data seems quite interesting. However, in my opinion, I think the analyses were somewhat inappropriate for the reasons stated above.

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Reviewer #1: No

Reviewer #2: No

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PONE-D-21-32417R1Difficulty and pleasure in the comprehension of verb-based metaphor sentences: a behavioral studyPLOS ONE

Dear Dr. Errington,

Thank you for submitting your revised manuscript to PLOS ONE.  I sent your revision to the two original reviewers and both believed your revisions to be quite responsive to their comments.  And I agree. However, they also raise a couple of final issues that I'd like you to address before your manuscript can be accepted for publication.  Both reviewers ask for additional clarification of Katz and Al-Azary's (2017) Semantic Neighborhood Density (SND) measure, and Reviewer 1 suggests providing some guidance for future research regarding the psychometric issues involved in assessing your construct.

Please submit your revised manuscript by Mar 07 2022 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.

Please include the following items when submitting your revised manuscript:

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Thomas Holtgraves, Ph.D.

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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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 #1: All comments have been addressed

Reviewer #2: (No Response)

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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 #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

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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 #1: Yes

Reviewer #2: 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 #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: I indicated that all of the present reviewer's comments have been addressed, but I still have qualms about how effectively two of those comments were addressed. First, although it is not possible to undo the difficulties created by a psychometrically thin and conceptually weak articulation of "affectiveness" (l. 94), "meaningfulness" (l. 639) etc., the authors would do well to say something about the steps that might be taken in future efforts to provide psychometric substance to the construct they are trying to assess. References to Shklovsky and Miall are not enough (e.g., is "strikingness" the same as "affectiveness"? how would we know?). Very briefly, please say how this psychometric issue might be addressed in future studies. Second, it is not clear that the authors have precisely coordinated their use of word2vec with the the DIFFERENTIATION that Katz and Al-Zary (2017) offer between (a) the distance between the vehicle and topic semantic neighborhoods and (b) the density of the separately considered vehicle and topic (l. 301). Is it possible to more precise about how these two aspects of metaphoric semantic structures are related to the procedures they rely on?

Reviewer #2: The authors have addressed the points I brought up in the last review. I think the manuscript looks excellent and will be very interesting to the PLoS ONE readership.

There is one small point of clarification about Katz and Al-Azary's (2017) Semantic Neighborhood Density (SND) measure. It is not exactly synonymous to semantic distance where two terms are compared, but rather, it is a measure of the average distance from a single term to its own neighbors. So, for a metaphor like "ski for office", SND doesn't actually measure the overlap between ski and office. Rather, it measures the semantic density of "ski" on its own and "office" on its own. If the sentence was "ski downhill", the SND for "ski" is still the exact same. It may indirectly get at overlap -- if "ski" and "office" both have high SND, then they may have more overlapping near neighbors, but SND on its own is not a measure of this. Just wanted to clarify this because the way it is written in the manuscript, it sounds like SND is a measure of the overlapping semantic neighbors between two terms.

They explain Semantic Neighborhood Density in a little more detail in this paper:

Al-Azary, H., McAuley, T., Buchanan, L., & Katz, A. N. (2019). Semantic processing of metaphor: A case-study of deep dyslexia. Journal of Neurolinguistics, 51, 297-308.

Thank you very much for the opportunity to review this work!

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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 #1: No

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.

Difficulty and pleasure in the comprehension of verb-based metaphor sentences: a behavioral study

PONE-D-21-32417R2

Dear Dr. Errington,

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,

Thomas Holtgraves, Ph.D.

Academic Editor

PLOS ONE

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