Pub Date : 2026-02-04DOI: 10.1177/08944393261421114
Conor Gaughan, Alexandru Cernat, Rachel Gibson, Marta Cantijoch, Riza Batista-Navarro
Survey research is entering a new era which centres on its linkage with other forms of digitally generated data such as social media. Many suggest that this can help to address existing weaknesses in self-report surveys such as non-response and measurement bias. However, to link a participant’s survey responses to their social media data, consent from the participant is required. Previous studies have shown that consent to linkage is typically low and selective. This paper expands on the existing literature by comparing Twitter (now X) usage and consent to survey linkage across five national contexts. Testing the effects of several sociodemographic and attitudinal predictors in the US, the UK, France, Germany and Poland, our study finds that overall consent rates vary significantly by age, political attention, privacy concern, trust in social media companies and frequency of political posting on Twitter/X. However, our results also confirm that variable effects differ significantly between nations, suggesting a moderating cultural influence. Within-country variation in the US between 2020 and 2024 is also present, indicating that effects are not necessarily fixed over time. These findings dictate the need for caution when conducting substantive comparisons across countries and time when using social media data.
{"title":"Who Consents to Sharing Their Tweets With Researchers? A Comparative Analysis of Selection Bias in Linked Survey and Social Media Data","authors":"Conor Gaughan, Alexandru Cernat, Rachel Gibson, Marta Cantijoch, Riza Batista-Navarro","doi":"10.1177/08944393261421114","DOIUrl":"https://doi.org/10.1177/08944393261421114","url":null,"abstract":"Survey research is entering a new era which centres on its linkage with other forms of digitally generated data such as social media. Many suggest that this can help to address existing weaknesses in self-report surveys such as non-response and measurement bias. However, to link a participant’s survey responses to their social media data, consent from the participant is required. Previous studies have shown that consent to linkage is typically low and selective. This paper expands on the existing literature by comparing Twitter (now X) usage and consent to survey linkage across five national contexts. Testing the effects of several sociodemographic and attitudinal predictors in the US, the UK, France, Germany and Poland, our study finds that overall consent rates vary significantly by age, political attention, privacy concern, trust in social media companies and frequency of political posting on Twitter/X. However, our results also confirm that variable effects differ significantly between nations, suggesting a moderating cultural influence. Within-country variation in the US between 2020 and 2024 is also present, indicating that effects are not necessarily fixed over time. These findings dictate the need for caution when conducting substantive comparisons across countries and time when using social media data.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"88 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146115664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-03DOI: 10.1177/08944393261419776
Paul Muya, Tabitha Onyinge
This study examines the impact of performatives and evolving social media typology in shaping political activism among Kenya’s Generation Z (Gen Z) movement during the 2024 anti-tax law protests. The study addresses the questions of the role of performatives and how social media has revolutionised their production, reproduction, and consumption in political activism in Kenya. Based on qualitative content analysis and critical discourse analysis, the study employed purposive sampling of a collection of digital artefacts, including memes, protest songs, TikTok videos, graffiti-inspired art, and Twitter threads, which were drawn from the #RejectFinanceBill2024 campaign. Analytical categories were derived from literature on performative activism, postcolonial media theory, and digital political communication. The findings suggest that Kenya’s Gen Z activists adopted a highly performative mode of social media resistance, blending entertainment with activism. The content of performatives was found to function not only as expressive tools but also as mechanisms for mobilising support, challenging state narratives, and asserting digital visibility. Social media was found to circumvent traditional media gatekeeping, amplifying the voices of the marginalised, and fostering an enlightened political culture. The study identifies a cyclic loop of production and reproduction of performatives, reinforcing African people’s communal identity formation and resistance posturing. Findings highlight how Gen Z’s social media use is reshaping civic engagement in the postcolonial public sphere. The study advances theoretical understanding of how visual and performative content is democratising political discourse, disrupting power hierarchies, and deepening participatory governance in the Global South. This study contributes to the body of literature on digital media and political communication by illuminating the intersection of social movement, culture, aesthetics, and performativities in resistance. These insights are particularly relevant for scholars and practitioners interested in digital media use, activism, political communication, and youth-led social movements.
{"title":"New Media, Meme Culture and Political Satire: The Role of Performative Art in Political Activism in Kenya","authors":"Paul Muya, Tabitha Onyinge","doi":"10.1177/08944393261419776","DOIUrl":"https://doi.org/10.1177/08944393261419776","url":null,"abstract":"This study examines the impact of performatives and evolving social media typology in shaping political activism among Kenya’s Generation Z (Gen Z) movement during the 2024 anti-tax law protests. The study addresses the questions of the role of performatives and how social media has revolutionised their production, reproduction, and consumption in political activism in Kenya. Based on qualitative content analysis and critical discourse analysis, the study employed purposive sampling of a collection of digital artefacts, including memes, protest songs, TikTok videos, graffiti-inspired art, and Twitter threads, which were drawn from the #RejectFinanceBill2024 campaign. Analytical categories were derived from literature on performative activism, postcolonial media theory, and digital political communication. The findings suggest that Kenya’s Gen Z activists adopted a highly performative mode of social media resistance, blending entertainment with activism. The content of performatives was found to function not only as expressive tools but also as mechanisms for mobilising support, challenging state narratives, and asserting digital visibility. Social media was found to circumvent traditional media gatekeeping, amplifying the voices of the marginalised, and fostering an enlightened political culture. The study identifies a cyclic loop of production and reproduction of performatives, reinforcing African people’s communal identity formation and resistance posturing. Findings highlight how Gen Z’s social media use is reshaping civic engagement in the postcolonial public sphere. The study advances theoretical understanding of how visual and performative content is democratising political discourse, disrupting power hierarchies, and deepening participatory governance in the Global South. This study contributes to the body of literature on digital media and political communication by illuminating the intersection of social movement, culture, aesthetics, and performativities in resistance. These insights are particularly relevant for scholars and practitioners interested in digital media use, activism, political communication, and youth-led social movements.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"41 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146115669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Supreme Court’s Dobbs v. Jackson Women’s Health Organization decision in June 2022 reversed 50 years of precedent by allowing states to formulate their own abortion policies. This resetting of abortion policy created a new raft of opportunities and threats across the states for both pro-life and pro-choice supporters. In this study, we aim to analyze how public discourse around abortion responded to this changed political context. Using a dataset of 288,325 abortion-related Tweets posted in 2022, we examine public reaction to Dobbs using both quantitative and qualitative approaches. We categorize Tweets by abortion stance (pro-choice and pro-life ) and geo-political context by state groups ( protected, restricted, and unsettled based on abortion access policy). Our temporal analysis shows that while both pro-choice and pro-life Twitter activity spiked after both the leaked draft in May 2022 and the final decision, only pro-choice discussions maintained a heightened level of engagement over time. Analyzing the discussion frames among the Tweets reveals that pro-choice users emphasized a wider range of arguments that varied by state context, while pro-life Tweets were generally unresponsive to state context. Our findings indicate that the new threats and opportunities had uneven effects within pro-life and pro-choice public discourse.
{"title":"States of Abortion Talk: Social Media Responses to Threats and Opportunities Post-Dobbs","authors":"Nafisa Nowshin, Kelsy Kretschmer, Glencora Borradaile","doi":"10.1177/08944393261421115","DOIUrl":"https://doi.org/10.1177/08944393261421115","url":null,"abstract":"The Supreme Court’s <jats:italic toggle=\"yes\">Dobbs v. Jackson Women’s Health Organization</jats:italic> decision in June 2022 reversed 50 years of precedent by allowing states to formulate their own abortion policies. This resetting of abortion policy created a new raft of opportunities and threats across the states for both pro-life and pro-choice supporters. In this study, we aim to analyze how public discourse around abortion responded to this changed political context. Using a dataset of 288,325 abortion-related Tweets posted in 2022, we examine public reaction to <jats:italic toggle=\"yes\">Dobbs</jats:italic> using both quantitative and qualitative approaches. We categorize Tweets by abortion stance <jats:italic toggle=\"yes\">(pro-choice</jats:italic> and <jats:italic toggle=\"yes\">pro-life</jats:italic> ) and geo-political context by state groups ( <jats:italic toggle=\"yes\">protected, restricted,</jats:italic> and <jats:italic toggle=\"yes\">unsettled</jats:italic> based on abortion access policy). Our temporal analysis shows that while both pro-choice and pro-life Twitter activity spiked after both the leaked draft in May 2022 and the final decision, only pro-choice discussions maintained a heightened level of engagement over time. Analyzing the discussion frames among the Tweets reveals that pro-choice users emphasized a wider range of arguments that varied by state context, while pro-life Tweets were generally unresponsive to state context. Our findings indicate that the new threats and opportunities had uneven effects within pro-life and pro-choice public discourse.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"46 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146115670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-31DOI: 10.1177/08944393261417730
Yuri Kasahara, Daniel Thilo Schroeder, Anis Yazidi, Pedro G. Lind
This study investigates the dynamics of anti-Muslim hate speech within Norwegian social media during the period between 2010 and 2021. Using a dataset of more than one million comments from Twitter and Facebook, we developed a custom hate speech classifier trained on an annotated corpus of 3,277 comments in Norwegian language. We identify that despite representing a small share of the total comments, hate speech content has increased over time. In an effort to understand the social network characteristics of hate speech content, we delve deeper into Twitter conversations as we can more easily identify how this content is spread. We develop network metrics to assess the prevalence, distribution, and diffusion of hateful content. The findings reveal that regardless of the number of users or tweets in a conversation, the volume of hateful content tends to remain constant. Furthermore, a small fraction of users contribute disproportionately to the dissemination of hate speech, with most conversations being limited in participant diversity. These results contribute to the growing field of computational social science by offering a novel methodology for studying hate speech in under-resourced languages and suggesting that mitigating hate speech may be possible through targeted network interventions rather than content removal alone.
{"title":"The Dynamics of Hate Speech: Assessing Anti-Muslim Hate Speech in Norwegian Social Media","authors":"Yuri Kasahara, Daniel Thilo Schroeder, Anis Yazidi, Pedro G. Lind","doi":"10.1177/08944393261417730","DOIUrl":"https://doi.org/10.1177/08944393261417730","url":null,"abstract":"This study investigates the dynamics of anti-Muslim hate speech within Norwegian social media during the period between 2010 and 2021. Using a dataset of more than one million comments from Twitter and Facebook, we developed a custom hate speech classifier trained on an annotated corpus of 3,277 comments in Norwegian language. We identify that despite representing a small share of the total comments, hate speech content has increased over time. In an effort to understand the social network characteristics of hate speech content, we delve deeper into Twitter conversations as we can more easily identify how this content is spread. We develop network metrics to assess the prevalence, distribution, and diffusion of hateful content. The findings reveal that regardless of the number of users or tweets in a conversation, the volume of hateful content tends to remain constant. Furthermore, a small fraction of users contribute disproportionately to the dissemination of hate speech, with most conversations being limited in participant diversity. These results contribute to the growing field of computational social science by offering a novel methodology for studying hate speech in under-resourced languages and suggesting that mitigating hate speech may be possible through targeted network interventions rather than content removal alone.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"80 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146098205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-30DOI: 10.1177/08944393261421118
Terri L. Towner, Caroline Muñoz
This study investigates which members of the 118th U.S. Congress adopt and use Threads and TikTok, and what political, demographic, and constituency-level characteristics explain this variation. Grounded in diffusion of innovation theory, we ask: What factors predict the adoption and use of these emerging platforms? We compiled original data on all members of Congress ( N = 535) by collecting social media account information from official congressional websites and manually verifying platform presence. Adoption was measured as a binary variable, and usage as the number of posts made through November 2023. Using probit and OLS regression models, we tested predictors including party affiliation, age, race, leadership status, and prior digital engagement. The empirical analyses reveal that Democrats and younger legislators are more likely to adopt Threads and TikTok. Prior digital engagement consistently predicts usage on both platforms. Notably, racial identity plays a critical role: non-white members are more likely to adopt and use TikTok, while white members are more likely to use Threads. This study offers the first empirical analysis of congressional adoption and usage of Threads and TikTok. Our findings demonstrate that platform choice is shaped by identity, institutional context, and political strategy. These findings offer new insights into the determinants of early platform adoption among U.S. congress members and the importance of aligning communication choices with constituent behavior and platform culture.
{"title":"Platform Politics in the U.S. Congress: Diffusion of TikTok and Threads","authors":"Terri L. Towner, Caroline Muñoz","doi":"10.1177/08944393261421118","DOIUrl":"https://doi.org/10.1177/08944393261421118","url":null,"abstract":"This study investigates which members of the 118th U.S. Congress adopt and use Threads and TikTok, and what political, demographic, and constituency-level characteristics explain this variation. Grounded in diffusion of innovation theory, we ask: What factors predict the adoption and use of these emerging platforms? We compiled original data on all members of Congress ( <jats:italic toggle=\"yes\">N</jats:italic> = 535) by collecting social media account information from official congressional websites and manually verifying platform presence. Adoption was measured as a binary variable, and usage as the number of posts made through November 2023. Using probit and OLS regression models, we tested predictors including party affiliation, age, race, leadership status, and prior digital engagement. The empirical analyses reveal that Democrats and younger legislators are more likely to adopt Threads and TikTok. Prior digital engagement consistently predicts usage on both platforms. Notably, racial identity plays a critical role: non-white members are more likely to adopt and use TikTok, while white members are more likely to use Threads. This study offers the first empirical analysis of congressional adoption and usage of Threads and TikTok. Our findings demonstrate that platform choice is shaped by identity, institutional context, and political strategy. These findings offer new insights into the determinants of early platform adoption among U.S. congress members and the importance of aligning communication choices with constituent behavior and platform culture.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"286 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146089854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-29DOI: 10.1177/08944393261421119
Justin Bonest Phillips, Timothy B. Gravelle, Andrea Carson, Mathew D. Marques
Unlike past studies that examine whether fact-checking can counter conspiratorial belief, we reverse the lens to investigate if fact-checking itself prompts conspiracy belief. Our study occurs in the days immediately preceding the 2024 US election. Shortly thereafter, Meta’s CEO Mark Zuckerberg abandoned Facebook’s third-party program altogether, arguing fact-checkers “have destroyed more trust than they have created.” We provide timely insight into fact-checking concerns using a preregistered online survey-based experiment of US Facebook users’ ( n = 2,409), randomly assigned to view either a generic Facebook fact-check (treatment) or a Facebook login screen. Results show no overall effects of third-party fact-checking on users’ propensity for conspiratorial beliefs. However, when individuals with high conspiracy mentality and strong conservative identification encounter a fact-check, they are more likely to endorse Facebook-related conspiracy beliefs. We also observe a three-way interaction among political independents with high and low conspiracy beliefs, where fact-checking potentially triggers or reduces such beliefs.
{"title":"Conspiracy or Public Service? Does Facebook’s Third-Party Fact-Checking Increase Conspiracy Beliefs Among Americans?","authors":"Justin Bonest Phillips, Timothy B. Gravelle, Andrea Carson, Mathew D. Marques","doi":"10.1177/08944393261421119","DOIUrl":"https://doi.org/10.1177/08944393261421119","url":null,"abstract":"Unlike past studies that examine whether fact-checking can counter conspiratorial belief, we reverse the lens to investigate if fact-checking itself prompts conspiracy belief. Our study occurs in the days immediately preceding the 2024 US election. Shortly thereafter, Meta’s CEO Mark Zuckerberg abandoned Facebook’s third-party program altogether, arguing fact-checkers “have destroyed more trust than they have created.” We provide timely insight into fact-checking concerns using a preregistered online survey-based experiment of US Facebook users’ ( <jats:italic toggle=\"yes\">n</jats:italic> = 2,409), randomly assigned to view either a generic Facebook fact-check (treatment) or a Facebook login screen. Results show no overall effects of third-party fact-checking on users’ propensity for conspiratorial beliefs. However, when individuals with high conspiracy mentality and strong conservative identification encounter a fact-check, they are more likely to endorse Facebook-related conspiracy beliefs. We also observe a three-way interaction among political independents with high and low conspiracy beliefs, where fact-checking potentially triggers or reduces such beliefs.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"55 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146070687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-27DOI: 10.1177/08944393251413277
Dan Bai, Yan Gu
Digital platforms now serve as crucial archives for analysing societal trends, yet their research APIs pose methodological challenges. This study critically evaluates TikTok Research API through comparative analysis of 6,373 videos from 14 creators in the United States and United Kingdom (2020–2022), contrasting API-derived outputs with manual collection and third-party analytics. The API demonstrated scalability, retrieving more videos than alternative methods and providing 22 variables, including eight unavailable elsewhere. However, limitations were substantial: transcriptions covered about 10% of the content, with more transcripts returned from American male creators. Engagement metrics exhibited inconsistent accuracy across data sources, with the API showing systematically lower view counts but higher comment and share counts compared to manual collection. The number of videos varied depending on sample composition, indicating that small changes in inclusion criteria could shift outcomes disproportionately. These results highlight systematic inconsistencies, showing why multi-method approaches remain necessary despite automation. While TikTok Research API offers valuable scale and ethical compliance, its demographic biases and metadata inconsistencies compromise validity. The study advocates integrated auditing protocols and targeted API refinements to improve representativeness and accuracy in platform-based research.
数字平台现在是分析社会趋势的重要档案，但它们的研究api带来了方法论上的挑战。本研究通过对美国和英国（2020-2022年）14位创作者的6373个视频进行对比分析，将API衍生的输出与人工收集和第三方分析进行了对比，批判性地评估了TikTok Research API。该API展示了可扩展性，比其他方法检索更多的视频，并提供22个变量，其中包括8个在其他地方不可用的变量。然而，限制是巨大的：转录覆盖了大约10%的内容，更多的转录来自美国男性创作者。用户粘性指标在不同数据源中呈现出不一致的准确性，与手动收集相比，API显示出较低的浏览次数，但较高的评论和分享次数。视频的数量因样本组成而异，这表明纳入标准的微小变化可能不成比例地改变结果。这些结果突出了系统的不一致性，显示了为什么尽管自动化仍然需要多方法方法。虽然抖音研究API提供了有价值的规模和道德合规，但它的人口统计偏见和元数据不一致损害了有效性。本研究提倡整合审计协议和有针对性的API改进，以提高基于平台的研究的代表性和准确性。
{"title":"Harnessing Big Data, Hindered by Bias: Evaluating TikTok Research API for Fair and Optimal Social Sciences","authors":"Dan Bai, Yan Gu","doi":"10.1177/08944393251413277","DOIUrl":"https://doi.org/10.1177/08944393251413277","url":null,"abstract":"Digital platforms now serve as crucial archives for analysing societal trends, yet their research APIs pose methodological challenges. This study critically evaluates TikTok Research API through comparative analysis of 6,373 videos from 14 creators in the United States and United Kingdom (2020–2022), contrasting API-derived outputs with manual collection and third-party analytics. The API demonstrated scalability, retrieving more videos than alternative methods and providing 22 variables, including eight unavailable elsewhere. However, limitations were substantial: transcriptions covered about 10% of the content, with more transcripts returned from American male creators. Engagement metrics exhibited inconsistent accuracy across data sources, with the API showing systematically lower view counts but higher comment and share counts compared to manual collection. The number of videos varied depending on sample composition, indicating that small changes in inclusion criteria could shift outcomes disproportionately. These results highlight systematic inconsistencies, showing why multi-method approaches remain necessary despite automation. While TikTok Research API offers valuable scale and ethical compliance, its demographic biases and metadata inconsistencies compromise validity. The study advocates integrated auditing protocols and targeted API refinements to improve representativeness and accuracy in platform-based research.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"44 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146056126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-24DOI: 10.1177/08944393261419793
Mariacristina Sciannamblo, Enrico Gandolfi
This article investigates the rhetorical dynamics emerging within Reddit communities, focusing on discussions surrounding the video game franchise The Last of Us . Building on the concept of procedural rhetoric, the paper suggests framing the collective articulation of meaning that emerges from the interaction between digital affordances—such as upvoting, moderation, and subreddit structures—and community practices in terms of “community rhetoric.” Drawing from a thematic analysis of posts and comments in two dedicated subreddits, the article identifies how content, attitude, and discursive climate shape participatory discourse. This framework is enriched by considering Reddit’s distinctive technical configurations, including pseudonymity and community self-governance, which foster specific discursive cultures. Rather than presenting Reddit as a neutral container, the study highlights how its infrastructural features actively mediate rhetorical production and sense-making. The paper contributes to digital rhetoric and media studies by offering a model that integrates platform affordances with user-driven cultural practices, showing how community engagement shapes knowledge, authority, and cultural narratives in online spaces. Limitations and future directions are discussed in light of applying the framework to other media fandoms and social platforms.
{"title":"Procedural Rhetorics Meet Platform Affordances: An Exploration of Community Rhetoric on Reddit","authors":"Mariacristina Sciannamblo, Enrico Gandolfi","doi":"10.1177/08944393261419793","DOIUrl":"https://doi.org/10.1177/08944393261419793","url":null,"abstract":"This article investigates the rhetorical dynamics emerging within Reddit communities, focusing on discussions surrounding the video game franchise <jats:italic toggle=\"yes\">The Last of Us</jats:italic> . Building on the concept of procedural rhetoric, the paper suggests framing the collective articulation of meaning that emerges from the interaction between digital affordances—such as upvoting, moderation, and subreddit structures—and community practices in terms of “community rhetoric.” Drawing from a thematic analysis of posts and comments in two dedicated subreddits, the article identifies how content, attitude, and discursive climate shape participatory discourse. This framework is enriched by considering Reddit’s distinctive technical configurations, including pseudonymity and community self-governance, which foster specific discursive cultures. Rather than presenting Reddit as a neutral container, the study highlights how its infrastructural features actively mediate rhetorical production and sense-making. The paper contributes to digital rhetoric and media studies by offering a model that integrates platform affordances with user-driven cultural practices, showing how community engagement shapes knowledge, authority, and cultural narratives in online spaces. Limitations and future directions are discussed in light of applying the framework to other media fandoms and social platforms.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"13 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146042673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-22DOI: 10.1177/08944393261419809
Sadullah Çelik, Cemile Zehra Köroğlu
Objective: This paper analyzes gender equality across countries in the year 2024 by using the GGGI, with the intention of disentangling the unseen structural and non-deterministic patterns. Instead of repeating the process of calculating the index, it is openly recognizing the compositional feature of the GGGI and the unseen similarities between the indices. Methods: This research employs a global cross-sectional study of 146 countries over the four primary GGGI sectors: economic participation, education, health and survival, and empowerment. Where OLS is only employed as a diagnostic test, as its almost perfect fit (R 2 ∼1) is squarely mechanical and lacks relevance for inference. Apart from ensemble models employed for predictions, K-means clustering, SHAP analysis, and GridSearchCV optimization are also used. Findings: The out-of-sample predictions demonstrate high levels of predictive accuracy, with Gradient Boosting models yielding an R 2 of approximately 0.90 and an RMSE of approximately 0.045, indicating that there is significant nonlinear information beyond index aggregation. Unsupervised clustering techniques show that there are seven distinct country clusters that go beyond traditional geographic and income divisions, which can be identified with more than 93% accuracy. The SHAP results show that empowerment and economic participation are drivers, while there is insignificant variation in healthcare. Contribution: This study identifies the boundaries of regression analysis in index research, as well as the advantages of machine learning analysis in determining structural patterns related to gender equity.
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Pub Date : 2026-01-21DOI: 10.1177/08944393261419796
Emre Can Kuran, Umut Kuran
Digital search platforms enable real-time observation of relationship distress through behavioral traces. This study tests whether Google Trends predicts official divorce rates in the United States, Germany, the Netherlands, and the United Kingdom from 2009 to 2023. We introduce Digital Behavioral Decoupling, in which online distress signals diverge from legal outcomes as divorce shifts from an institutional procedure to an emotionally mediated digital phenomenon. Methods include unit root tests, cointegration analysis, Granger causality, spectral coherence, and rolling-origin nowcasting. Search queries are grouped into pre-divorce (cognitive distress), during-divorce (procedural action), and post-divorce (emotional recovery) phases. Results show 62.5% of terms lead divorce rates by 1–2 years, yet only 8.3% remain significant after False Discovery Rate correction. The Netherlands demonstrates 100% forecast improvements beyond autoregressive models (DM 2.87–3.43, p < 0.02) across all search terms, from early relationship therapy queries through procedural and post-divorce searches, indicating systematic capture of the entire divorce pathway. Germany shows intermediate results with 33% forecast success beyond autoregressive benchmarks (DM 2.40–2.81) limited to problem-recognition terms, suggesting episodic crisis-driven engagement. The United States and United Kingdom show no forecast gains beyond autoregressive models despite high search volumes, consistent with information saturation in normalized divorce cultures. Lead-lag relationships are frequency-specific, concentrated at 3–5 year periodicities. Findings link family sociology with affective computing and provide a replicable toolkit for tracking relationship dissolution in algorithmically curated information environments.
数字搜索平台可以通过行为痕迹实时观察人际关系的困扰。这项研究测试谷歌Trends是否预测了美国、德国、荷兰和英国从2009年到2023年的官方离婚率。我们介绍了数字行为脱钩，其中，随着离婚从一种制度程序转变为一种情感介导的数字现象，网上的痛苦信号与法律结果不同。方法包括单位根检验、协整分析、格兰杰因果关系、谱相干性和滚动起源临近预测。搜索查询分为离婚前（认知痛苦）、离婚中（程序行动）和离婚后（情绪恢复）三个阶段。结果显示，62.5%的条款导致离婚1-2年，但只有8.3%的条款在错误发现率修正后仍然重要。从早期的关系治疗查询到程序和离婚后的搜索，荷兰证明了100%的预测改进，超越了自回归模型（DM 2.87-3.43, p < 0.02），表明系统地捕获了整个离婚途径。德国表现出了中等水平的结果，在自回归基准（DM 2.40-2.81）之外，预测成功率为33%，这一指标仅限于问题识别方面，表明了偶发性危机驱动的参与。尽管搜索量很高，但美国和英国没有显示出超出自回归模型的预测收益，这与规范化离婚文化中的信息饱和一致。超前-滞后关系是频率特异性的，集中在3-5年的周期。研究结果将家庭社会学与情感计算联系起来，并提供了一个可复制的工具包，用于在算法策划的信息环境中跟踪关系的解散。
{"title":"From Search to Separation: Digital Behavioral Decoupling and the Predictive Power of Google Trends for Divorce Outcomes Across Four Western Nations","authors":"Emre Can Kuran, Umut Kuran","doi":"10.1177/08944393261419796","DOIUrl":"https://doi.org/10.1177/08944393261419796","url":null,"abstract":"Digital search platforms enable real-time observation of relationship distress through behavioral traces. This study tests whether Google Trends predicts official divorce rates in the United States, Germany, the Netherlands, and the United Kingdom from 2009 to 2023. We introduce Digital Behavioral Decoupling, in which online distress signals diverge from legal outcomes as divorce shifts from an institutional procedure to an emotionally mediated digital phenomenon. Methods include unit root tests, cointegration analysis, Granger causality, spectral coherence, and rolling-origin nowcasting. Search queries are grouped into pre-divorce (cognitive distress), during-divorce (procedural action), and post-divorce (emotional recovery) phases. Results show 62.5% of terms lead divorce rates by 1–2 years, yet only 8.3% remain significant after False Discovery Rate correction. The Netherlands demonstrates 100% forecast improvements beyond autoregressive models (DM 2.87–3.43, p < 0.02) across all search terms, from early relationship therapy queries through procedural and post-divorce searches, indicating systematic capture of the entire divorce pathway. Germany shows intermediate results with 33% forecast success beyond autoregressive benchmarks (DM 2.40–2.81) limited to problem-recognition terms, suggesting episodic crisis-driven engagement. The United States and United Kingdom show no forecast gains beyond autoregressive models despite high search volumes, consistent with information saturation in normalized divorce cultures. Lead-lag relationships are frequency-specific, concentrated at 3–5 year periodicities. Findings link family sociology with affective computing and provide a replicable toolkit for tracking relationship dissolution in algorithmically curated information environments.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"396 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146014415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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