Bluesky: Network topology, polarization, and algorithmic curation

Dorian Quelle; Alexandre Bovet

doi:10.1371/journal.pone.0318034

Peer Review History

Original SubmissionAugust 9, 2024
9 Aug 2024 Author Response https://doi.org/10.1371/journal.pone.0318034.r001
27 Sep 2024 Decision Letter - Francesco Pierri, Editor PONE-D-24-33584Bluesky: Network Topology, Polarization, and Algorithmic CurationPLOS ONE Dear Dr. Quelle, 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 Nov 02 2024 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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You also have the option of uploading the data as Supporting Information files, but we would recommend depositing data directly to a data repository if possible. We will update your Data Availability statement on your behalf to reflect the information you provide. Additional Editor Comments: Dear authors, R1 is a bit more critical of your work while R2 is very positive about the paper. I recommend you address carefully the concerns of the former, and where you do not agree with their suggestions, provide a clear and well-reasoned explanation to justify your approach. [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: No Reviewer #2: Yes ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: No 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: This paper performs several studies on a large dataset of Bluesky activity. Since most of the studies are exploratory analyses, the content of the paper does not add much to what is the current literature on this platform. There are several points that should be explored more, it would be good to do fewer studies going into detail without stopping at an EDA. In Abstract and Discussion (lines 391, 392, 393) sections there are some statements “Bluesky provides unprecedented research opportunities” and “Bluesky enables researchers to answer old questions with a novel treasure trove of data that could contribute to a range of scientific open questions” that should be supported by more concrete studies and comparisons against other platforms to identify any patterns. Before claiming these things it would be appropriate to study the contents in detail (type of content shared, types of activities, characteristics of accounts) comparing them with what the literature offers. The section «Evolution of the Bluesky Network» (from line 114) does not show a true evolution of the network but rather shows a high-level study of how it is composed and its statistics, I would suggest changing the name to “Analysis of the Bluesky Network.” The «Feed» section is very interesting and it should be better studied. In the «Political Leaning & Polarization of Bluesky» (from line 229) section domains and their political leanings are studied using MBFC. In Table 4 it is stated that “To filter automated accounts, we exclude posts from accounts with more than 10,000 posted URLs.”, it would be a very good thing to make a comparison between a study that excluded them and one that included them, to motivate this choice. Also, there is no citation to any work showing that automated accounts are those with more than 10,000 posted URLs. It would also be helpful to show how many domains were given a score as a percentage of the totals; I expect that many of the shared domains are not on MBFC and it would be good to report the relative figure. The paper mentions «algorithmic curation mechanisms» but there are no detailed studies on the algorithm. It would be good to do some in-depth studies on this issue or remove the do from the paper and title. Figures should be redone taking into account any color blindness Reviewer #2: This paper provides a in-depth analysis of the advent of Bluesky, from its inception in February 2023 to current days. After providing an overview of the user activity on the platform, the authors discuss how Bluesky benefited from controversial events in Twitter's management. The authors also look at the overall political leaning of the user base on Bluesky, by looking at the links that are overly shared on the platform. They also nuance their results by looking at the discussion around the conflict in Gaza. This case study shows a more polarised interaction network on the platform. This paper provides a robust analysis of an emerging social media platform. The authors offer a comprehensive overview of Bluesky's functionalities and user base, both with their analysis of user activity and their active contribution to the algorithmic processes on Bluesky. Moreover, their analysis of political partisanship on Bluesky is very clear and nuanced, looking at different perspectives to understand how Bluesky users consume information and interact with users with similar political leanings. Finally, their analysis of the discourse around the conflict in Gaza provides the reader with a very interesting case study, as it highlights how the public opinions shifts over time and leads to siloed communities in the interaction network. Overall, this research paper is novel, provides a robust analysis and is extremely interesting to read throughout. I therefore suggest it to be accepted for publication at PLOS One. Before it gets published, I would advise the authors to correct two small typos in the paper, that might impact its readability to the reader: - Page 8, line 246: Your text lacks a reference to a section, as it says "As shown in section ," - Page 9, line 272: You mention 8,409 million links, but I imagine you meant to say 8 million links, according to table 4? ****** 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. 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Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0318034.r002
Revision 1
19 Nov 2024 Author Response Dear Editor and Reviewers, We thank you for the helpful reviews and the chance to revise and resubmit our manuscript. We considered all of the points you raised, which considerably improved our work. Please find below a summary of the changes we made, followed by a detailed answer to each reviewer. Summary of Changes In response to reviewer feedback, we have made several changes to improve the manuscript's clarity, methodology, and accessibility. We include added sections in this letter and have highlighted them in the submitted manuscript. The key modifications are detailed below: Method & Data Compliance We have enhanced our Methods section to clearly articulate our adherence to data source terms and conditions. The manuscript now explicitly states that "Our dataset collection and analysis methods were designed to respect user privacy and platform terms. All data analyzed in this study consists only of public posts and user information accessed through standard API requests, in compliance with Bluesky's Terms of Service." We further clarify that "The data was collected using standard API endpoints available to all users, and no special access privileges were required or utilized." we have deposited the codes and user IDs that can be used to download all the data necessary to reproduce our results directly from the Bluesky API on an open data repository accessible at https://doi.org/10.7910/DVN/NGQKDS. Document Formatting and Style All sections and subsections have been altered to title case for consistency with journal requirements. Figure references throughout the manuscript have been corrected to ensure proper citation. Additional information regarding Terms of Service has been included in the Methods section to provide greater clarity on data collection and usage. Structure and Clarity We have renamed section "Evolution of the Bluesky Network" to "Structure and Evolution of the Bluesky Network" to better reflect both static and dynamic aspects of our analysis. Additionally, we fixed an empty reference on page 8, line 246 and corrected a numerical error on page 9, line 272 regarding link count. Data Analysis and Methodology We have provided detailed justification for the 10,000 URL posting threshold used to filter automated accounts in this response. Our analysis shows that only 48 accounts were removed, yet these accounts were responsible for 15.30% of all URLs shared. We demonstrated that this removal had minimal impact on political (20.7% vs 18.81%) and questionable source (0.14% vs 0.13%) distributions, as shown in the comparative tables in this response. Furthermore, our analysis of MBFC domain coverage shows that 1.29% of unique domains have associated ratings, while this number increases to 21.77% for domains shared by multiple users. To reflect this analysis in the manuscript, we have added a summary paragraph justifying this methodological choice. Enhanced Feed Analysis We have expanded the feed analysis section with new insights. This includes a topic modeling analysis of feed descriptions and a new table showing top topics by number of feeds and likes. We have added an analysis of feed creation patterns and user engagement and enhanced our discussion of democratized content curation mechanisms. Accessibility We have reviewed and justified color choices in figures for colorblind accessibility. We believe Figure 1 uses a colorblind-friendly combination, while Figure 7 now includes white patterns to improve category differentiation. We believe Figures 8 \& 10 are accessible due to their luminance-based visualization, and we believe Figure 9's existing color scheme and format provides appropriate accessibility. These revisions address all points raised by the reviewers. We are grateful for the time invested by both reviewers which we believe has significantly improved both the technical clarity and accessibility of the manuscript. Reviewer 1 1) This paper performs several studies on a large dataset of Bluesky activity. Since most of the studies are exploratory analyses, the content of the paper does not add much to what is the current literature on this platform. There are several points that should be explored more, it would be good to do fewer studies going into detail without stopping at an EDA. We thank the reviewer for their thoughtful feedback on our manuscript. We would like to explain our rationale for the current structure of the paper. This work presents the first comprehensive analysis of Bluesky's complete network structure and evolution. Given the novelty of the platform and the access to its complete data, we believe a broad exploratory analysis provides necessary foundational insights for future research. While the reviewer correctly notes that many of our analyses are exploratory, this approach has allowed us to map the fundamental characteristics of this new platform and its novel features like decentralized content curation. Importantly, our broad analytical approach has enabled us to uncover several unexpected findings that might have been missed with a narrower focus, particularly the interesting contrast between political homogeneity and issue-specific polarization. Moreover, following the Reviewer's suggestion, we added a novel analysis of the feed usage (see answer below). 2) The section «Evolution of the Bluesky Network» (from line 114) does not show a true evolution of the network but rather shows a high-level study of how it is composed and its statistics, I would suggest changing the name to "Analysis of the Bluesky Network." We appreciate the reviewer's attention to the precise characterization of our analysis. While the section does contain structural statistics and compositional analysis, it also tracks the temporal evolution of the network from February 2023 to May 2024, including changes in user activity, network density, clustering coefficients, and path lengths over time. To better reflect this dual nature of our analysis, we modified the section title to "Structure and Evolution of the Bluesky Network", which more accurately capture both the static and dynamic aspects of our investigation. 3) In the «Political Leaning \& Polarization of Bluesky» (from line 229) section domains and their political leanings are studied using MBFC. In Table 4 it is stated that "To filter automated accounts, we exclude posts from accounts with more than 10,000 posted URLs.", it would be a very good thing to make a comparison between a study that excluded them and one that included them, to motivate this choice. Also, there is no citation to any work showing that automated accounts are those with more than 10,000 posted URLs. It would also be helpful to show how many domains were given a score as a percentage of the totals; I expect that many of the shared domains are not on MBFC and it would be good to report the relative figure. We thank the reviewer for their thoughtful suggestion about validating our URL filtering threshold. We agree that this methodological choice deserves clear justification to help readers understand its impact on our analysis. We have added a summary paragraph to the revised manuscript explaining our rationale and demonstrating that the filtering has minimal impact on our key findings. We decided to remove accounts which posted more than 10,000 URLs to prevent a small number of accounts having an undue influence over the distribution of URLs that we document. This cutoff removed only 48 accounts from the entire dataset. However, these 48 accounts were responsible for 15.30% of URLs shared on the platform. While we are not allowed to provide any directly identifying data in line with our ethics statements, we will provide a brief summary of the function of these accounts. They primarily represent automated news aggregators, RSS feed bots, and content syndication services across multiple platforms. The accounts predominantly focus on aggregating and redistributing news content, transportation updates, sports information, and media coverage from various sources in multiple languages. We add a table to this review detailing the changes in the distribution by keeping the accounts. [Tables] In total, the removal of the 48 automated accounts removes over a million shared URLs from the dataset. In contrast, the proportion of political (20.7\% vs. 18.81\%) and questionable sources (0.14\% vs. 0.13\%) remains relatively constant. We highlight the domains which have been added to the dataset by altering the cutoff. The reviewer furthermore inquired what percentage of "domains were given a score". The relative number of domains that have a rating is detailed in the table. However, this does not refer to unique domains, and we agree with the reviewer that this is an important statistic to mention in the manuscript. Only 1.29% of unique domains shared in the dataset have an associated rating while representing approximately 20% of the URLs shared. This shows that the political domains (i.e., news sites) are shared significantly more than other domains on the website. Among domains that have been shared by at least two users, the percentage of unique domains that have a rating rises to 21.77%. To summarise this analysis, we added the following paragraph on pages 10 & 11 of the manuscript: "Our analysis excludes posts from accounts that shared more than 10,000 URLs (n=48 accounts), which primarily represent automated news aggregators and content syndication services. The top domains shared by the 48 accounts are globo.com (a Brazilian news network, 176K shares), osintukraine.com (a war documentation and fact-checking site, 94K shares), yahoo.co.jp (a Japanese web portal, 82K shares), 9to5mac.com (an Apple news site, 60K shares), and lemonde.fr (a French newspaper, 48K shares). While these accounts contributed 15.30\% of all URLs in the dataset, their removal had minimal impact on the overall distribution of content sources, with political sources shifting from 20.70\% to 18.81\% and questionable sources remaining nearly constant (0.13\% to 0.14\%). Though only 1.29\% of unique domains in our dataset have an MBFC rating, this coverage increases substantially to 21.77\% when considering domains shared by multiple users. In other words, the small subset of websites that were news and political sources (those with MBFC ratings) were shared dramatically more often than non-rated websites across the platform." 4) The «Feed» section is very interesting and it should be better studied. The paper mentions «algorithmic curation mechanisms» but there are no detailed studies on the algorithm. It would be good to do some in-depth studies on this issue or remove the do from the paper and title. We agree with the reviewer that the ability of Bluesky users to generate and subscribe to a diverse range of feeds deserves more in-depth research. As elaborated in response to the reviewer's first criticism, our paper does not intend to inhibit future research and does not claim to study all aspects of feeds. However, as we agree with the reviewer that this section might leave readers wanting, we decided to expand the section and have added the following content. QUOTE: "To systematically analyze both the creation and popularity of different content curation approaches, we translate all feed descriptions to English with Google translate and create a topic model of the descriptions. We employed BERTopic (Grootendorst, 2022) for neural topic modeling on the feed descriptions after translating them to English using Google Translate. Feed descriptions were preprocessed by removing URLs, HTML tags, numeric tokens, and non-Latin characters. Using the all-MiniLM-L6-v2 sentence transformer model (Reimers, 2020), our analysis identified 463 distinct topics. Of these, 56.84\% of feeds were grouped into topics containing multiple feeds, while the remainder were single-feed topics. The largest topics based on feed count and total likes received are detailed in table \ref{tab:topics}. [Table] The most prevalent topic category (Topic 0) consists of art-focused feeds ($n=612$). These feeds aggregate content from artists, and aim to connect artists online. For example, one feed described itself as "Find your artist friends here!". Similarly, the second most prevalent cluster (Topic 1) consists of users sharing "Music, Songs, and Audio" (n = 394). The third largest cluster filters for content on games, particularly board games (n=390). The next topic is related to Japanese pop culture, anime, gaming, and fandom-related feeds, with a particular focus on specific characters, series, or creators, often written in a mix of Japanese romanization and English. Other interesting feed-topics include NSFW content (Topic 4, n=354) and Manga (Topic 9, n=330). Interestingly, the largest topics by feed count do not correlate strongly with the topics that received the most likes. Only topic 2 (n_likes = 4,260) is represented in this list. The two largest cluster of feeds based on the number of likes is a cluster entirely composed of "furry" related feeds. Topic 331 with 5,308 likes consist of feeds which filter content based on social connections and user interactions, like "Posts liked by your follows'' or "The last post from each user you follow". They help users discover content through their social graph and highlight engagement patterns, such as "Posts from your quieter followers" and "Most popular posts by people you follow". Many of these feeds aim to surface community content and relationship dynamics, like "Posts that are popular with people you follow". This topic and topic 28 both deal with non-content related filtering. While topic 331 focuses on the social graph of Bluesky, topic 28 shows feeds primarily focused on engagement-based filtering, particularly around likes. These feeds include various ways to surface content based on engagement metrics, from simple filters like "Posts with more than 1000 likes" to more complex sorting like "Most likes and reposts within 24 hours." Some feeds focus on high engagement ("over 10000 Likes"), while others combine engagement metrics with time windows and language filters. The feeds help users discover trending and highly engaged content through different combinations of these parameters. Our analysis reveals that users leverage Bluesky's algorithmic curation capabilities in diverse and creative ways. While traditional engagement-based feeds exist (surfacing highly-liked or trending content), many feeds serve specific community purposes. Some create topic-focused spaces around art, anime, or gaming interests, while others build dedicated safe spaces for marginalized communities (evidenced by popular LGBTQ+ feeds with 3,327 likes). The data shows significant engagement with feeds focused on community building and content discovery, whether through social graph analysis ("Posts liked by your follows") or interest-based curation ("Find your artist friends here!"). The broad range of moderation approaches on Bluesky enables users to craft these specialized spaces while maintaining platform-wide standards, demonstrating how democratized content curation can effectively serve both broad discovery needs and niche community interests. Our analysis suggests this approach has enabled both broad content discovery and specialized community engagement." END QUOTE 5) Figures should be redone taking into account any color blindness. We appreciate the reviewer shares our concern for accessibility. We will address each plot that uses two distinct colors within one panel in the following list: [Table] Reviewer 2 1) This paper provides a in-depth analysis of the advent of Bluesky, from its inception in February 2023 to current days. After providing an overview of the user activity on the platform, the authors discuss how Bluesky benefited from controversial events in Twitter's management. The authors also look at the overall political leaning of the user base on Bluesky, by looking at the links that are overly shared on the platform. They also nuance their results by looking at the discussion around the conflict in Gaza. This case study shows a more polarised interaction network on the platform. 2) This paper provides a robust analysis https://doi.org/10.1371/journal.pone.0318034.r003
8 Jan 2025 Decision Letter - Francesco Pierri, Editor Bluesky: Network Topology, Polarization, and Algorithmic Curation PONE-D-24-33584R1 Dear Dr. Quelle, 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 will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, 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, Francesco Pierri, Ph.D. Academic Editor PLOS ONE Additional Editor Comments (optional): 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: All comments have been addressed ******** 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: (No Response) ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: (No Response) ****** 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: (No Response) ****** 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: (No Response) ****** 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: All points have been properly considered, the changes are in line with what has been commented on, making the work complete Reviewer #2: (No Response) ****** 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: Yes: Gianluca Nogara Reviewer #2: No ******** https://doi.org/10.1371/journal.pone.0318034.r004
Formally Accepted
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