Peer Review History

Original SubmissionDecember 3, 2025
Decision Letter - José Luiz Vieira, Editor

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Dear Dr. Guo,-->-->

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.

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ACADEMIC EDITOR: -->-->

Dear Dr. Guo,

After a careful review of your manuscript, I believe that minor revisions  are required to address a few outstanding questions. Based on the PLOS ONE  editorial criteria, we recommend the following changes:

1. A brief review of past work should be included so as to make connect with the study which was carried.

2. At some places the proper flow is missing, for eg each study should clearly reflect to which extent the aim of study(1-4) was met.

3. A brief comparison of this work should also be added with the existing ones.

4. The conclusion should describe how this study is beneficial as a whole for the society.-->-->Best regards-->-->Jose luiz vieira

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José Luiz Fernandes Vieira

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Reviewers' comments:

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1. Is the manuscript technically sound, and do the data support the conclusions?

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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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Reviewer #1: 1. A brief review of past work should be included so as to make connect with the study which was carried.

2. At some places the proper flow is missing, for eg each study should clearly reflect to which extent the aim of study(1-4) was met.

3. A brief comparison of this work should also be added with the existing ones.

4. The conclusion should describe how this study is beneficial as a whole for the society.

Reviewer #2: Methodologically, the article is robust. The use of six experiments allows not only to establish causality, but also to identify boundary conditions; also they developed a simulator based on Python and HTML5 that mimics real platforms such as TikTok or Twitch, increasing the realism of the experience for the participant.

As well, the study separates public from private engagement, allowing for a more nuanced understanding of how social status influences different types of user actions.

Traditionally, parasocial interaction was studied as a one-to-one relationship. This research justifies the shift to a “one-and-a-half-sided” relationship model, which recognizes the presence of third parties in the content consumption process. It is pertinent the use of SCT to explain how differential treatment acts as a “relational thermostat” that triggers threats or boosts to the viewer's self-esteem.

In terms of results, the article reveals a counterintuitive benefit to “fair” rejection; for example, rejecting a bad suggestion can increase the engagement of other viewers by reinforcing positive social comparison. It suggests that streamers should stop viewing their channel as thousands of individual relationships and start managing it as a social ecology where every interaction is public and shared.

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Reviewer #1: Yes: Dr. Ankita Srivastava

Reviewer #2: No

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Revision 1

Response to Reviewer #1

Dear Reviewer #1,

Thank you sincerely for your careful reading of our manuscript and your constructive feedback. Your comments have been instrumental in improving the clarity, coherence, and scholarly rigor of our work. Below, we provide a point-by-point response to each of your comments, detailing the specific revisions we have made.

Reviewer Comment 1:

A brief review of past work should be included so as to make connect with the study which was carried.

Response:

We greatly appreciate this suggestion. We agree that a dedicated literature review is essential for establishing the theoretical foundation and connecting it to our empirical studies.

In the revised manuscript, we have added a new section titled “Literature Review” between the Introduction and the Materials and Methods sections. This section is organized into four subsections:

(a) Parasocial Interaction and Live Streaming Engagement

This subsection traces the evolution of Parasocial Interaction (PSI) theory from its origins in Horton and Wohl (1956) and the operationalization by Rubin et al. (1985), through recent applications in live streaming contexts (e.g., Lee et al., 2024; Yen et al., 2024; Huang, 2025). We highlight the shift toward community-level perspectives, particularly the “one-and-a-half-sided” model proposed by Kowert and Daniel (2021), and identify the gap our study addresses: the lack of empirical models quantifying how witnessed third-party interactions affect the focal viewer.

(b) Social Comparison Theory in Digital Environments

This subsection reviews Festinger's (1954) foundational theory and its extension by Buunk and Gibbons (2007), followed by key empirical findings on social comparison effects in digital media, including self-esteem impacts on social media (Vogel et al., 2014; Le Blanc-Brillon et al., 2025), downward comparison effects (Rüther et al., 2023), and social media envy (Liu et al., 2024). We identify the gap that existing research has focused on static platforms, not real-time interactive environments.

(c) Leader-Member Exchange (LMX) Differentiation

This subsection reviews the LMX differentiation literature, including the meta-analytic evidence (Martin et al., 2016), conceptual clarifications (Martin et al., 2018), relative LMX effects (Lee et al., 2019), and team-level consequences (Choi et al., 2020; Liden et al., 2006). We draw the novel parallel between leader-member and streamer-viewer dynamics.

(d) Hypotheses Development

We have added a dedicated subsection that explicitly states all seven hypotheses (H1-H7) with their theoretical grounding, providing a clear link between the reviewed literature and our empirical studies.

Additionally, we have added three foundational references to strengthen the review: Rubin et al. (1985) on the PSI scale, Buunk and Gibbons (2007) on social comparison orientation, and Liden et al. (2006) on LMX differentiation.

Changes Made:

A new “Literature Review” section with four subsections has been inserted between the Introduction and Materials and Methods. Three new references have been added to the bibliography.

Reviewer Comment 2:

At some places the proper flow is missing, for eg each study should clearly reflect to which extent the aim of study(1-4) was met.

Response:

Thank you for this important observation. We acknowledge that the original manuscript did not sufficiently connect each study's findings back to our overarching research aims, which may have disrupted the reader's ability to follow the logical progression of our research program.

In the revised manuscript, we have improved the flow by explicitly mapping each study to the newly formalized hypotheses (H1-H7) developed in the Literature Review section. We have added clear orienting and concluding sentences to the Results section of each study:

Study 1 now opens by stating it examined whether witnessed peer interactions influence focal viewer engagement beyond personal preference (H1) and whether PCD mediates this relationship (H2), and explicitly concludes that H2 is supported, indicating that PCD causally mediates the impact.

Study 2 opens by stating it tested whether the nature of the streamer (Emotional vs. Utility) moderates the PCD effect (H3), and concludes that the results support H3 and indicate that streamer type is an important contextual boundary condition.

Study 3 opens by testing whether the effect is conditional on the viewer's affective disposition (H4), and closes by noting these results support H4 and suggest that viewer disposition serves as an individual-level boundary condition.

Study 4 opens by testing whether the peer's group identity moderates the impact of PCD (H5), and clarifies the mechanism by concluding these findings support H5a and H5b.

Study 5 delineates the behavioral scope by distinguishing between public/social and private/financial engagement types (H6), concluding that PCD primarily relates to public, reputation-based behaviors.

Study 6 addresses long-term outcomes, opening by examining whether PCD relates to streamer trustworthiness and viewer loyalty through perceived trust (H7), and concludes that it extends the analysis beyond immediate engagement to longer-term relational outcomes.

By explicitly stating the hypothesis being tested at the outset of each study and confirming whether it was supported at the conclusion, we believe the reader can now easily track how each study sequentially builds on the previous one to fulfill our research aims.

Changes Made:

Explicit hypothesis-linking opening and concluding sentences have been highlighted in all six Study subsections in the Results section.

Reviewer Comment 3:

A brief comparison of this work should also be added with the existing ones.

Response:

We thank the reviewer for this suggestion. We agree that a systematic comparison with existing work strengthens the positioning of our contribution.

We have added a new subsection titled “Comparison with Existing Literature” in the Discussion section. This subsection compares our findings with key prior studies across four dimensions:

(a) Relationship model

We compare our empirical quantification of the triadic dynamic (Self-Streamer-Peer) with the conceptual proposal by Kowert and Daniel (2021), noting that our study is the first to operationalize and causally test the “one-and-a-half-sided” relationship model.

(b) Social comparison in digital environments

We compare our real-time, experimental approach with the correlational, static-platform studies by Vogel et al. (2014) and Liu et al. (2024), highlighting that our PCD construct captures the immediate, vivid comparison unique to live streaming.

(c) LMX differentiation

We compare our cross-application of organizational theory to the consumer/media context with the workplace-focused studies by Lee et al. (2019) and Choi et al. (2020), noting that our effect sizes in the emotional streaming context are comparable to or larger than those in organizational settings.

(d) Trust-loyalty pathway

We compare our finding that fairness (not just intimacy) drives trust with the PSI-to-trust models of Kim et al. (2025) and Tian et al. (2023), distinguishing our experimental manipulation of fairness from their correlational approaches.

Changes Made:

A new “Comparison with Existing Literature” subsection has been added to the Discussion section.

Reviewer Comment 4:

The conclusion should describe how this study is beneficial as a whole for the society.

Response:

We appreciate this valuable suggestion. We agree that articulating the broader societal implications of our research is important for demonstrating its relevance beyond academic and industry contexts.

We have added a substantial new paragraph at the end of the Conclusion section that addresses four dimensions of societal benefit:

(a) Digital well-being and mental health

We discuss how PCD reveals that unfair treatment in live streams can threaten viewers' self-esteem and psychological well-being, contributing to the growing evidence on social media's mental health impact. We argue that awareness of PCD mechanisms can inform the design of healthier digital platforms.

(b) Platform governance and policy

We note that our findings provide empirical grounds for platform policies and algorithmic tools that can flag or mitigate visible favoritism, reducing social-comparative harm.

(c) Digital literacy

We argue that understanding PCD dynamics can contribute to digital literacy education, equipping users, particularly younger audiences, with the knowledge to recognize and resist social comparison traps in interactive media.

(d) Equity in the creator economy

We highlight that the “silent majority” of viewers can be systematically disadvantaged by streamer behaviors that privilege a vocal minority, with implications for fairness in digital labor, consumption, and community participation.

Changes Made:

A new paragraph on broader societal implications has been added at the end of the Conclusion section.

We hope that these revisions adequately address all of your concerns. We are grateful for your constructive feedback, which has significantly strengthened the manuscript. We remain open to any further suggestions you may have.

Response to Reviewer #2

Dear Reviewer #2,

Thank you very much for your thoughtful review and for your highly encouraging assessment of our manuscript. We are deeply grateful for the time you took to read our work and for your precise, insightful summary of our methodology and theoretical contributions.

Reviewer Comment:

Methodologically, the article is robust. The use of six experiments allows not only to establish causality, but also to identify boundary conditions; also they developed a simulator based on Python and HTML5 that mimics real platforms such as TikTok or Twitch, increasing the realism of the experience for the participant. As well, the study separates public from private engagement, allowing for a more nuanced understanding of how social status influences different types of user actions.

Traditionally, parasocial interaction was studied as a one-to-one relationship. This research justifies the shift to a “one-and-a-half-sided” relationship model, which recognizes the presence of third parties in the content consumption process. It is pertinent the use of SCT to explain how differential treatment acts as a “relational thermostat” that triggers threats or boosts to the viewer's self-esteem.

In terms of results, the article reveals a counterintuitive benefit to “fair” rejection; for example, rejecting a bad suggestion can increase the engagement of other viewers by reinforcing positive social comparison. It suggests that streamers should stop viewing their channel as thousands of individual relationships and start managing it as a social ecology where every interaction is public and shared.

Response:

We sincerely thank you for this incredibly positive and accurate synthesis of our core arguments. It is highly rewarding to see that our methodological choices, particularly the custom live-streaming simulator, and our theoretical shift toward a “one-and-a-half-sided” community ecology resonated so strongly with you.

While we are thrilled by your positive evaluation, we recognize that this study is only an initial step in unraveling the complexities of community dynamics in live streaming. Your comments have reinforced our commitment to this line of inquiry, and we aim to remain humble regarding the scope of our current findings.

As we look to the future, your summary inspires us to push this research forward in several directions to address the inevitable limitations of our current lab-based design. Specifically, our subsequent work will focus on:

Field Validation: Moving beyond the simulator to conduct field studies on actual platforms (e.g., scraping real-time chat logs to correlate gifting/subscription behaviors with streamer “shout-outs”).

Longitudinal Dynamics: While our current study captures an acute, single instance of Perceived Closeness Difference (PCD), we plan to investigate the effects of chronic or consistent PCD (e.g., the long-term impact on a viewer who is repeatedly ignored).

Complex Group Dynamics: We hope to deepen our exploration of social identity by examining more complex inter-group dynamics, such as intense rivalries between different fan “cliques” within a single streamer’s channel.

Affective Mediators: We plan to explicitly measure specific emotional mediators, such as envy or jealousy, which we suspect are the direct affective drivers bridging the cognitive PCD evaluation and the resulting behavioral engagement.

Once again, we wish to express our profound gratitude for your supportive review. Your endorsement gives us great confidence in the value of treating digital channels as interconnected social ecologies rather than merely collections of isolated dyads.

Sincerely,

Huichao Guo, on behalf of Runhua Huang

Attachments
Attachment
Submitted filename: response_reviewer2.pdf
Decision Letter - José Luiz Vieira, Editor

Behind the Screen: Unraveling the Role of Perceived Closeness Difference in Shaping Viewers’ Engagement Behaviors

PONE-D-25-63717R1

Dear Dr. Guo

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,

José Luiz Fernandes Vieira

Academic Editor

PLOS One

Formally Accepted
Acceptance Letter - José Luiz Vieira, Editor

PONE-D-25-63717R1

PLOS One

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Academic Editor

PLOS One

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