PONE-D-21-22972A Dataset for the Study of Identity at Scale: Annual Prevalence of American Twitter Users with specified Token in their Profile Bio 2015-2020PLOS ONE

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Academic Editor

PLOS ONE

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Reviewers' comments:

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Reviewer #1: Yes

Reviewer #2: Yes

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

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

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Reviewer #1: The paper presents a valuable contribution regarding the use of online data to study the evolution of social trends in the US over the 2015-2020 time frame. The author precisely describes the methodology used to compile the dataset, the metrics developed to analyze it, and shows a few research avenues that could be investigated through this data.

While the language used by the author is clear and precise, the structure of the article could sometimes be clarified. Some methodological elements are defined several times over the article (such as the calculation of prevalence, page 7 and again page 14). The section on "Longitudinal Online Profile Sampling" appears after the presentation of the dataset. The paper could be improved with a more rigorous separation of sections such as data collection, metrics, online tool, examples ...

The simple tokenisation approach described in the article (separation over word boundaries) seems to provide interesting results. However, some classic linguistic methods such as lemmatization could be investigated to study not only one given form of a term ("kitty", "kitties", "kitten") but all the form of a given term ("kitt-" or even "cat-"). Such process could be an interesting addition to the dataset.

Finally, I have to point out that the name and URL of the online tool infringe the anonymity of the author. When submitting this kind of paper through a peer review process, the name of the tool should be anonymized and the URL should only be integrated in the final version.

Reviewer #2: Review of

A Dataset for the Study of Identity at Scale: Annual Prevalence of American Twitter - Users with specified Token in their Profile Bio 2015-2020

I have read and reviewed ‘A Dataset for the Study of Identity at Scale: Annual Prevalence of American Twitter. Users with specified Token in their Profile Bio 2015-2020’. This article provides information about a new method and data set to study self-reported self-concept via the Twitter bio, and trends therein. The article is written very well and describes an interesting and relevant method for analyzing trends in the way people chose to present themselves.

And in this last sentence lies my only major criticism of the present article: it strikes me as purely descriptive, and would benefit from a little more background with regard to the theme of self-concept. The references the author gives on this topic seem incomplete. I would personally recommend a bit more information about what type of self-representation a Twitter bio would constitute on the basis of literature on the topic of self-categorization and generally the psychology of identity. I would suggest the literature listed (incompletely!) below. Without more information about the psychology of how and why people chose to represent themselves in the way they do, the analysis is rather superficial and only describes trends (‘winners and losers’), in my opinion. To add any sort of meaning to those trends, I think more background is needed.

This would also provide more insight into questions about to what degree the medium, Twitter, influences the way in which people choose to represent themselves.

To be perfectly clear: my remarks are only valid if the author intended to not only introduce the dataset, and the data collection method, but also decribe how this data can be analyzed. If not, than the article is concise and short description of said aspects.

In sum: the author describes an interesting and potentially promising method for collecting self-reported data on identity. The article is well written and the used methods are sound. As a reviewer I feel however, that a more complete discussion of the relevant literature on self-identity, self-categorization and self-representation would help to better appreciate the value of the collected data.

Suggested literature:

Lea, M., Spears, R., & De Groot, D. (2001). Knowing me, knowing you: Anonymity effects on social identity processes within groups. Personality and Social Psychology Bulletin, 27(5), 526-537.

Reicher, S. D., Haslam, S. A., Spears, R., & Reynolds, K. J. (2012). A social mind: The context of John Turner’s work and its influence. European review of social psychology, 23(1), 344-385.

Thumim, N. (2012). Self-representation and digital culture. Springer.

Van Zomeren, M., Postmes, T., & Spears, R. (2008). Toward an integrative social identity model of collective action: a quantitative research synthesis of three socio-psychological perspectives. Psychological bulletin, 134(4), 504.

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Reviewer #1: No

Reviewer #2: No

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A dataset for the study of identity at scale: Annual Prevalence of American Twitter Users with Specified Token in their Profile Bio 2015-2020

PONE-D-21-22972R1

Dear Dr. Jones,

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.

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Kind regards,

Liviu-Adrian Cotfas

Academic Editor

PLOS ONE

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