Social Science Computer Review最新文献

{"title":"Managing Conti: Temporal Dynamics of Managerial Communication in a Ransomware Group","authors":"Giovanni Radhitio Putra Sadewo, David Bright, Chad Whelan, Jürgen Lerner","doi":"10.1177/08944393261478555","DOIUrl":"https://doi.org/10.1177/08944393261478555","url":null,"abstract":"Ransomware groups are frequently described as structured enterprises with defined managerial hierarchies, yet most empirical research adopts cross-sectional designs that treat leadership positions as static. This study asks: How do upper- and middle-management actors in a ransomware organisation adjust their communication patterns over time, particularly in balancing coordination and concealment? Focusing on the Conti ransomware group, we examine whether managerial centrality and rank-based communication preferences remain stable or shift across different operational phases. We analyse leaked Jabber chat logs comprising 95,134 cleaned message events exchanged among 287 unique user IDs between June 2020 and March 2022. Actors were classified into upper management ( <jats:italic toggle=\"yes\">n</jats:italic> = 9), middle management ( <jats:italic toggle=\"yes\">n</jats:italic> = 9), staff ( <jats:italic toggle=\"yes\">n</jats:italic> = 81), and affiliates/unassigned ( <jats:italic toggle=\"yes\">n</jats:italic> = 188). The data were divided into four temporal periods. Using relational event models (REMs) estimated via Cox proportional hazard models with sampled non-events, we model rank-based sending, receiving, and homophily/heterophily effects, interacting these mechanisms with time to capture period-specific dynamics. The findings indicate that upper management was highly active in sending and receiving messages during the early stage of operations, but subsequently withdrew from routine communication. Despite reduced visibility, upper managers consistently exhibited cross-rank (heterophilous) communication rather than insulating themselves through same-rank ties. Middle management, by contrast, remained consistently active across most periods and alternated between cross-rank and same-rank communication patterns, reflecting a flexible intermediary role. Overall, managerial centrality did not persist uniformly over time. This study contributes to the literature by advancing a dynamic, longitudinal perspective on ransomware governance. It demonstrates that managerial embeddedness is temporally contingent and tier-specific, underscoring the importance of event-level and rank-based network analysis. The findings also inform disruption strategies by identifying when and which managerial tiers are most structurally central, highlighting stage-specific vulnerabilities in ransomware organisations.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"19 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148768349","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}

{"title":"Where You Are Is What You Get! Inconsistencies of Digital Trace Data across Download Locations","authors":"Johanna Hölzl, Florian Keusch, John Collins","doi":"10.1177/08944393261469494","DOIUrl":"https://doi.org/10.1177/08944393261469494","url":null,"abstract":"To collect digital trace data, researchers continue to rely on for-profit companies’ Application Programming Interfaces (APIs). These APIs often return samples of the data based on intransparent sampling procedures and algorithms. In this paper, we extend research on the reliability of digital trace data from APIs by examining the effect of the download location on inconsistencies across returned samples: Do we get different values from digital trace data APIs depending on where we download the data from? We compare samples from Google Trends, YouTube Data, and the New York Times (NYT) API from four countries across three continents (Austria, Germany, the U.S., and Australia) for the same query parameters (i.e., search term, region, and time range). Our results show that the download location impacts the returned samples for all three APIs, depending on the query. We find large inconsistencies for samples from Google Trends and the YouTube Data API, while the NYT API returns identical article sets from each download location for most queries. We conclude with practical recommendations for researchers using these APIs. Our findings serve as a cautionary reminder for social scientists relying on sampling-based APIs as they point to yet another limitation regarding their reliability and reproducibility.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"19 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148650550","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}

{"title":"Does Negativity Pay Off? The Impact of Political Party Attributes on the Use and Performance of Negative Campaigning in Digital Political Advertising","authors":"Hanna Paulke, Simon Kruschinski, Márton Bene, Jörg Haßler, Daniel Jackson, Darren Lilleker, Melanie Magin, Uta Russmann","doi":"10.1177/08944393261469406","DOIUrl":"https://doi.org/10.1177/08944393261469406","url":null,"abstract":"While research has shown how different political actors adapt engagement-triggering strategies in organic election campaigns on social media platforms, we know little about how such strategies are used in paid political advertising and how they affect algorithmic ad performance. To address this gap, this study analyzes how party attributes shape spending on, impressions of, and the cost efficiency of negative campaigning in digital political advertising. Manually content-analyzing all Facebook ads from 48 parties across 10 countries during the European Parliament election in 2019, we find that, on average, parties do not allocate more resources to negative ads, which also do not achieve higher impression counts and are even associated with higher costs per 1,000 impressions (cost efficiency). However, party characteristics matter: Whereas opposition parties invest more in negative campaigning and consequently gain more impressions than government parties, negativity only pays off in terms of cost efficiency for extreme parties. Our findings contribute to a better understanding of the interplay between advertiser characteristics and content strategies in shaping ad use and performance within commercial marketing infrastructure, emphasizing the need for greater transparency to ensure fair competition in digital political advertising.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"28 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148499102","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}

{"title":"Profiling Digital Hate: A Multidimensional Measurement Approach Based on the Perspective API","authors":"Thomas Kirchmair, Kevin Koban, Jörg Matthes","doi":"10.1177/08944393261469403","DOIUrl":"https://doi.org/10.1177/08944393261469403","url":null,"abstract":"The automatic classification of digital hate is a pressing challenge, yet many existing computational models remain opaque and insufficiently evaluated as measurement tools in social science contexts. This study examines the utility of Google’s Perspective API as a measurement instrument by modeling higher-order constructs of harmful discourse (i.e., incivility and intolerance) as outcomes of multiple lower-level behavioral indicators captured by distinct API scores rather than using a single aggregate score as a proxy for complex social behaviors while enabling the evaluation of state-of-the-art black-box classifiers beyond classification metrics. Drawing on 4,000 manually annotated English-language YouTube comments in the context of the Israel-Hamas war, we test whether multiple API scores predict incivility and intolerance using generalized linear and additive models, assess classification performance across non-hateful, uncivil, and intolerant content, and benchmark a recent deep learning model. Results show that <jats:italic toggle=\"yes\">Identity Attack</jats:italic> is a strong predictor of intolerance, whereas <jats:italic toggle=\"yes\">Insult</jats:italic> and <jats:italic toggle=\"yes\">Profanity</jats:italic> are indicative of incivility. While classification performance is somewhat below state-of-the-art deep learning models, our approach offers important advantages: transparency, interpretability, accessibility for non-technical researchers, and potential cross-linguistic applicability. We argue that typology-driven, multi-indicator-based classification provides a practical and theoretically grounded complement to more aggregated black-box models, particularly in human-in-the-loop workflows that can help reduce annotator exposure through pre-filtering of content.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"319 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148416745","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}

{"title":"Modular Polyvocality: Community Detection and Semantic Analysis of Civil Society Discourse in English-Language #MahsaAmini Twitter Networks","authors":"Hossein Masoudnia, Alireza Samiee Esfahani, Mohsen Forghani, Mohammad Moghimi, Hossein Samiei Esfahany","doi":"10.1177/08944393261460815","DOIUrl":"https://doi.org/10.1177/08944393261460815","url":null,"abstract":"This study investigates how English-language Twitter discourse surrounding the #MahsaAmini protests (October 2022–February 2023) organized into distinct yet interconnected thematic communities within civil society networks. Combining Louvain community detection, sentiment profiling (via VADER), and semantic validation (Jensen–Shannon Divergence, MANOVA, cosine similarity), we map five protest “streams” reflecting modular issue alignments, from Documentation of events involving violence and On-the-Ground Mobilization to Monarchist Advocacy &amp; Diaspora Political Engagement and Anti-IRGC Campaigns. While these communities differ in topical focus, their shared affective tone and overlapping lexicons point to modular polyvocality, a discourse structure characterized by thematic differentiation within broader rhetorical and affective coherence. This pattern represents polyvocal consensus rather than fragmentation. We interpret these findings through the lens of connective action, networked publics, and digital diaspora activism, arguing that the discourse reflects a transnational, modular, and affectively aligned subset of protest-oriented civil society mobilization within constrained information environments. This work contributes to debates on hybrid dissent, algorithmic visibility, and the structure of protest discourse in controlled digital contexts.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"226 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148401472","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}

{"title":"Automating Content Analysis With Multiple LLM Agents: Impacts of Agent Attributes and Human–AI Collaboration","authors":"Xinyan Zhao, Chengshuai Zhao, Mordecai Mengesteab, Chau-Wai Wong, Mengqi Zhan, Zhen Tan, Tianlong Chen","doi":"10.1177/08944393261465001","DOIUrl":"https://doi.org/10.1177/08944393261465001","url":null,"abstract":"Emerging research in computational social science has applied LLMs to automate content analysis, often by prompting a single model to act as a human coder. While a single LLM may suffice for a few manifest variables, it still falls short on diverse latent constructs. And the impact of LLM agent attributes on measurement outcomes remains unclear, limiting their validity for communication research. Drawing upon the literature on interacting agents and communication, this study examines the impact of agent diversity, agent open-mindedness, and human–AI collaboration (HAIC) in a multi-LLM-agent system for automated content analysis. The results demonstrate reliable and accurate measurement of four communication variables across three datasets, with improved performance following agent discussion. Additionally, agent open-mindedness, but not agent diversity, significantly affects measurement outcomes. These results highlight the potential of multi-LLM-agent systems for automated content analysis and suggest the importance of considering agent attributes and values in system design.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"31 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148379881","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}

{"title":"From Trivial to Meaningful: The Moderating Role of Perceived Satisfaction in the Relationship Between Incidental Exposure and Political Participation","authors":"Jinwan Kim, Melissa R. Gotlieb","doi":"10.1177/08944393261465004","DOIUrl":"https://doi.org/10.1177/08944393261465004","url":null,"abstract":"Scholars have studied the relationship between incidental exposure (i.e., encountering political information unintentionally) and political participation. Nevertheless, the dynamic processes relating incidental exposure to political participation remain unclear. Building upon the political incidental news exposure (PINE) and social media political participation (SMPP) models, this study ( <jats:italic toggle=\"yes\">N</jats:italic> = 702) examines first- and second-level incidental exposure and its relationship to low-effort online and high-effort political participation. Furthermore, it examines whether perceived satisfaction from low-effort online participation moderates the relationship between incidental exposure and high-effort participation. Results suggest that second-level incidental exposure relates to greater low-effort online participation, which, in turn, opens a pathway to high-effort participation, especially when individuals perceive such participation as satisfying and able to address social and political issues. These findings provide a nuanced understanding of the pathways from incidental exposure to political participation, contributing to the broader literature on political communication and behavior in the digital age.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"53 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148321808","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}

{"title":"Artificial Intelligence in Government Weakens Citizens’ Affective Ties With Public Employees: Results From a Vignette Experiment","authors":"Pascal D. Koenig, Sveinung Arnesen","doi":"10.1177/08944393261461566","DOIUrl":"https://doi.org/10.1177/08944393261461566","url":null,"abstract":"This article examines how citizens’ perceptions of public employees in the education system change as these employees adopt artificial intelligence (AI) in their work. It argues that the use of AI matters for citizens’ perceptions of decision-making not only due to AI system characteristics, but also because AI adoption alters the perceived relationship between citizens and public organizations. Rooted in assumptions of social cognition theory, the analysis tests how information about AI use by public employees alters the perceived warmth of these employees and thereby affects the acceptability of decision-making. The analysis is based on a pre-registered vignette experiment and a sample of 4,569 participants from Norway. It finds that AI use decreases both the perceived warmth and competence of public employees, that these evaluations negatively bear on the overall acceptability of decision-making, and that the effect of AI use is stronger for public employees more directly interacting with others.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"51 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148299364","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}

{"title":"From Fragmented Narratives to Systemic Critiques: Long-Term Transformations in Korean Twitter Discourse on Sexual Violence","authors":"Ji-Myoung Choi, Hye-Won Choi, Chico Q. Camargo","doi":"10.1177/08944393261451724","DOIUrl":"https://doi.org/10.1177/08944393261451724","url":null,"abstract":"This study examines how the #MeToo movement reshaped long-term public discourse on sexual violence in South Korea. While research has documented the surge of attention following prosecutor Seo Ji-hyun’s 2018 disclosure, little is known about how the movement reorganized the broader discursive field beyond the initial moment of crisis. Drawing on discursive institutionalism, we argue that #MeToo acted as a discursive shock that consolidated previously fragmented conversations into more coherent and durable interpretive frameworks. Using an 8-year corpus of 351,582 Korean-language tweets (2015–2023), we apply Dirichlet Multinomial Regression topic modeling and time-series analysis to identify shifts in both topical content and discursive structure. Our findings show a transition from episodic, emotion-driven narratives to stable, thematic frames emphasizing human rights, systemic discrimination, and institutional accountability. We further demonstrate increasing convergence between social media and mainstream news, indicating diffusion and stabilization of these new frames. The results suggest that digital activism can produce enduring transformations in public meaning, illuminating how social movements institutionalize discourse over time.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"8 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148285492","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}

{"title":"Expression of Concern: “Exploring the Dark Tetrad in Human–GenAI Relationships: A Multi-Source Evaluation of GenAI Abuse”","authors":"","doi":"10.1177/08944393261460956","DOIUrl":"https://doi.org/10.1177/08944393261460956","url":null,"abstract":"","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"37 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148385891","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}