Pub Date : 2025-04-19DOI: 10.1177/08944393251332640
Timilehin Durotoye, Manuel Goyanes, Rosa Berganza, Homero Gil de Zúñiga
Prior research has largely documented the overall mobilizing effects of social media news consumption and political discussion linked to citizens’ political participatory behaviors. However, limited empirical research has considered the informational and communicative effects to be contingent upon different social media platforms. Therefore, this study advances distinct theoretical affordances and effects of social media news use on online (by using online versions of legacy media outlets, blogs, and news apps) and social media political participation. Taking advantage of US comparative panel data, ordinary least squares (OLS) causal autoregressive regressions and panel autoregressive structural equation model tests cast a much-needed light on the diverse effects of Facebook, X, Snapchat, WhatsApp, Instagram, YouTube, and Reddit use for news over both political discussions with weak and strong ties, and political participation online and in social media. Moreover, results from two-step algorithmic cluster analysis clarify how these social media platforms generate different information and political behavior clusters of citizens, which also provide a comparative view of how social media platforms differently contribute to people’s public and political life in US democracy.
{"title":"Online and Social Media Political Participation: Political Discussion Network Ties and Differential Social Media Platform Effects Over Time","authors":"Timilehin Durotoye, Manuel Goyanes, Rosa Berganza, Homero Gil de Zúñiga","doi":"10.1177/08944393251332640","DOIUrl":"https://doi.org/10.1177/08944393251332640","url":null,"abstract":"Prior research has largely documented the overall mobilizing effects of social media news consumption and political discussion linked to citizens’ political participatory behaviors. However, limited empirical research has considered the informational and communicative effects to be contingent upon different social media platforms. Therefore, this study advances distinct theoretical affordances and effects of social media news use on online (by using online versions of legacy media outlets, blogs, and news apps) and social media political participation. Taking advantage of US comparative panel data, ordinary least squares (OLS) causal autoregressive regressions and panel autoregressive structural equation model tests cast a much-needed light on the diverse effects of Facebook, X, Snapchat, WhatsApp, Instagram, YouTube, and Reddit use for news over both political discussions with weak and strong ties, and political participation online and in social media. Moreover, results from two-step algorithmic cluster analysis clarify how these social media platforms generate different information and political behavior clusters of citizens, which also provide a comparative view of how social media platforms differently contribute to people’s public and political life in US democracy.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"37 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143849603","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 : 2025-04-14DOI: 10.1177/08944393251333365
Gi Woong Yun, Sung-Yeon Park
Theoretical frameworks Resource-Based View (RBV) and competitive advantages have served as conceptual foundations for investigating the role of Google Maps in business success. This research has two key findings: First, an analysis of a dataset obtained by scraping local business information from Google Maps ( N = 9,445) shows that minority-owned businesses were less likely to be claimed on Google Maps and received fewer consumer review comments compared to their non-minority counterparts. Second, a comparison of Google Maps data collected before the outbreak of the COVID-19 pandemic in 2019 and follow-up data gathered in 2022 reveals higher survival rates among businesses that were claimed, utilized business attributes, or had more reviews. Together, these findings suggest that a stronger presence on Google Maps contributed to competitive advantages and business survival during the pandemic. This underscores the importance of Google Maps presence for the survival of businesses during a crisis.
{"title":"Minority-Owned, Claimed Status, and Profile Attributes of Businesses on Google Maps: COVID-19 Pandemic Survival","authors":"Gi Woong Yun, Sung-Yeon Park","doi":"10.1177/08944393251333365","DOIUrl":"https://doi.org/10.1177/08944393251333365","url":null,"abstract":"Theoretical frameworks Resource-Based View (RBV) and competitive advantages have served as conceptual foundations for investigating the role of Google Maps in business success. This research has two key findings: First, an analysis of a dataset obtained by scraping local business information from Google Maps ( <jats:italic>N</jats:italic> = 9,445) shows that minority-owned businesses were less likely to be claimed on Google Maps and received fewer consumer review comments compared to their non-minority counterparts. Second, a comparison of Google Maps data collected before the outbreak of the COVID-19 pandemic in 2019 and follow-up data gathered in 2022 reveals higher survival rates among businesses that were claimed, utilized business attributes, or had more reviews. Together, these findings suggest that a stronger presence on Google Maps contributed to competitive advantages and business survival during the pandemic. This underscores the importance of Google Maps presence for the survival of businesses during a crisis.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"122 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143832266","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 : 2025-04-04DOI: 10.1177/08944393251331510
Mar Castillo-Campos, David Becerra-Alonso, Hajo G. Boomgaarden
Media bias has long been a subject of scholarly interest due to its potential to shape public perceptions and behaviors. This systematic review leverages advances in natural language processing (NLP) to explore automated methods to detect media bias, addressing five core questions: it examines the definitions and operationalization of media bias, explores the NLP tasks addressed for its detection, the technologies used, and their respective outcomes and applied findings. This review also examines the practical applications of these methodologies and assesses the patterns, implications, and limitations associated with using artificial intelligence for media bias detection. Analyzing peer-reviewed articles from 2019 to 2023, the review initially identified 519 articles, which ultimately included 28 relevant ones. Significant heterogeneity is observed in bias definitions, affecting the analysis and detection approaches. The review highlights the predominant use of some methods and identifies challenges such as inconsistencies in problem definition, outcome measurement, and comparative method evaluation. Regardless of the conceptualizations of bias and the methods used, studies consistently identify bias in media outlets. Thus, studying media bias remains necessary for raising awareness and detection, and NLP methods are significant allies in this endeavor. This research aims to consolidate the foundations of recent advances in NLP for bias detection, encouraging researchers to focus on developing transparent, task-specific tools and work toward a consensus on a technical definition of bias and standardized metrics for its evaluation.
{"title":"Automated Detection of Media Bias Using Artificial Intelligence and Natural Language Processing: A Systematic Review","authors":"Mar Castillo-Campos, David Becerra-Alonso, Hajo G. Boomgaarden","doi":"10.1177/08944393251331510","DOIUrl":"https://doi.org/10.1177/08944393251331510","url":null,"abstract":"Media bias has long been a subject of scholarly interest due to its potential to shape public perceptions and behaviors. This systematic review leverages advances in natural language processing (NLP) to explore automated methods to detect media bias, addressing five core questions: it examines the definitions and operationalization of media bias, explores the NLP tasks addressed for its detection, the technologies used, and their respective outcomes and applied findings. This review also examines the practical applications of these methodologies and assesses the patterns, implications, and limitations associated with using artificial intelligence for media bias detection. Analyzing peer-reviewed articles from 2019 to 2023, the review initially identified 519 articles, which ultimately included 28 relevant ones. Significant heterogeneity is observed in bias definitions, affecting the analysis and detection approaches. The review highlights the predominant use of some methods and identifies challenges such as inconsistencies in problem definition, outcome measurement, and comparative method evaluation. Regardless of the conceptualizations of bias and the methods used, studies consistently identify bias in media outlets. Thus, studying media bias remains necessary for raising awareness and detection, and NLP methods are significant allies in this endeavor. This research aims to consolidate the foundations of recent advances in NLP for bias detection, encouraging researchers to focus on developing transparent, task-specific tools and work toward a consensus on a technical definition of bias and standardized metrics for its evaluation.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"38 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143782658","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 : 2025-03-24DOI: 10.1177/08944393251328309
Kenneth Bunker
This study examines electoral forecasting in volatile party systems, focusing on factors contributing to deviations between poll predictions and actual election outcomes. Using Italy as a case study, it identifies biases in polling data and proposes a method to enhance estimator accuracy in a context of stable institutions and volatile electoral dynamics. Data from three Italian general elections are analyzed to evaluate discrepancies between pre-electoral polls and results, assessing key factors such as timing of data collection, survey methodology, sample size, and party system fragmentation. Employing a Bayesian inference process via a Markov chain Monte Carlo (MCMC) adaptive Metropolis-Hastings (MH) algorithm, the study demonstrates that pre-electoral estimates can be significantly improved using the Two-Stage Model (TSM). By consistently outperforming traditional poll predictions, the TSM offers a robust framework for addressing polling biases. These findings advance political forecasting by improving accuracy in both consolidated democracies and volatile electoral contexts, while emphasizing the need for future research on dynamic polling methods and fundamentals-based models.
{"title":"Electoral Forecasting in Volatile Party System Settings: Assessing and Improving Pre-Election Poll Predictions in Italy","authors":"Kenneth Bunker","doi":"10.1177/08944393251328309","DOIUrl":"https://doi.org/10.1177/08944393251328309","url":null,"abstract":"This study examines electoral forecasting in volatile party systems, focusing on factors contributing to deviations between poll predictions and actual election outcomes. Using Italy as a case study, it identifies biases in polling data and proposes a method to enhance estimator accuracy in a context of stable institutions and volatile electoral dynamics. Data from three Italian general elections are analyzed to evaluate discrepancies between pre-electoral polls and results, assessing key factors such as timing of data collection, survey methodology, sample size, and party system fragmentation. Employing a Bayesian inference process via a Markov chain Monte Carlo (MCMC) adaptive Metropolis-Hastings (MH) algorithm, the study demonstrates that pre-electoral estimates can be significantly improved using the Two-Stage Model (TSM). By consistently outperforming traditional poll predictions, the TSM offers a robust framework for addressing polling biases. These findings advance political forecasting by improving accuracy in both consolidated democracies and volatile electoral contexts, while emphasizing the need for future research on dynamic polling methods and fundamentals-based models.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"183 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143695280","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 : 2025-03-14DOI: 10.1177/08944393251326175
Steve Randerson, Thomas Graydon-Guy, En-Yi Lin, Sally Casswell
Large language models show promising capability in some qualitative content analysis tasks; however, research reporting their performance in identifying initial codes that underpin subsequent analysis is scarce. This paper explores the suitability of GPT-4 to assist in building a codebook for a discourse network analysis (DNA) of a recent alcohol policy reform. DNA is a codebook-driven approach to identifying groupings of actors who use similar policy framings. The paper uses GPT-4 to identify initial codes (‘concepts’) and related quotes in 108 news articles and interviews. The results produced by GPT-4 are compared to a codebook prepared by researchers. GPT-4 identified over two-thirds of the concepts found by the researchers, and it was highly accurate in screening out a large volume of irrelevant media items. However, GPT-4 also provided many irrelevant concepts that required researcher review and removal. The discussion reflects on the implications for using GPT-4 in codebook preparation for DNA and other situations, including the need for human involvement and sample testing to understand its strengths and limitations, which may limit efficiency gains.
{"title":"Exploring the Use of a Large Language Model for Inductive Content Analysis in a Discourse Network Analysis Study","authors":"Steve Randerson, Thomas Graydon-Guy, En-Yi Lin, Sally Casswell","doi":"10.1177/08944393251326175","DOIUrl":"https://doi.org/10.1177/08944393251326175","url":null,"abstract":"Large language models show promising capability in some qualitative content analysis tasks; however, research reporting their performance in identifying initial codes that underpin subsequent analysis is scarce. This paper explores the suitability of GPT-4 to assist in building a codebook for a discourse network analysis (DNA) of a recent alcohol policy reform. DNA is a codebook-driven approach to identifying groupings of actors who use similar policy framings. The paper uses GPT-4 to identify initial codes (‘concepts’) and related quotes in 108 news articles and interviews. The results produced by GPT-4 are compared to a codebook prepared by researchers. GPT-4 identified over two-thirds of the concepts found by the researchers, and it was highly accurate in screening out a large volume of irrelevant media items. However, GPT-4 also provided many irrelevant concepts that required researcher review and removal. The discussion reflects on the implications for using GPT-4 in codebook preparation for DNA and other situations, including the need for human involvement and sample testing to understand its strengths and limitations, which may limit efficiency gains.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"56 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143627418","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 : 2025-02-25DOI: 10.1177/08944393251322160
Hana Vonkova, Ondrej Papajoanu, Martin Bosko
Understanding reporting behavior in questionnaires is a key issue in enhancing cross-national data comparability and policy decisions. Computers help improve the analysis of careless or insufficient effort (C/IE) responding by logging response times and other response behavior, ensuring data quality. We introduce a response-time based approach, built on an analysis of the relationship between a survey item and a related external variable, to cross-national research. Using PISA 2015 data from 58 countries/economies, we analyze patterns of correlations between the enjoyment of science and science test scores across response time. We focus on C/IE responding towards the beginning of the response time spectrum. Results indicate rather diligent responding in Eastern Asia and a part of Northern Europe. Yet in other regions (e.g., part of Latin America and the Caribbean, and Eastern Europe), C/IE responding might be distorting the data. We provide other researchers with information regarding when and to what extent C/IE responding can occur across countries. We enhance the understanding of heterogeneity in reporting behavior across countries.
{"title":"Response Times and Self-Reporting: Response Patterns Across Countries and World Regions Using Data From a Large Scale Computer-Based Assessment","authors":"Hana Vonkova, Ondrej Papajoanu, Martin Bosko","doi":"10.1177/08944393251322160","DOIUrl":"https://doi.org/10.1177/08944393251322160","url":null,"abstract":"Understanding reporting behavior in questionnaires is a key issue in enhancing cross-national data comparability and policy decisions. Computers help improve the analysis of careless or insufficient effort (C/IE) responding by logging response times and other response behavior, ensuring data quality. We introduce a response-time based approach, built on an analysis of the relationship between a survey item and a related external variable, to cross-national research. Using PISA 2015 data from 58 countries/economies, we analyze patterns of correlations between the enjoyment of science and science test scores across response time. We focus on C/IE responding towards the beginning of the response time spectrum. Results indicate rather diligent responding in Eastern Asia and a part of Northern Europe. Yet in other regions (e.g., part of Latin America and the Caribbean, and Eastern Europe), C/IE responding might be distorting the data. We provide other researchers with information regarding when and to what extent C/IE responding can occur across countries. We enhance the understanding of heterogeneity in reporting behavior across countries.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"37 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143528373","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 : 2025-02-24DOI: 10.1177/08944393251320059
Brandon C. Bouchillon
Research indicates that prejudice has been growing in America. Citizens feel increasingly threatened by immigrants, and hate crimes against immigrant groups have risen. Declining interpersonal contact has also made it more difficult to address prejudice directly. This study examines whether nonpolitical social media groups can foster connections that reduce prejudice. These groups allow users to connect on the basis of shared interests, enabling diverse individuals to form close relationships which may improve attitudes toward immigrants. Using a national web survey matched to U.S. Census percentages for sex, race, ethnicity, age, and region of residence ( N = 1500), along with a two-wave panel conducted over six weeks ( N = 752), results indicate that blatant prejudice is more prevalent than subtle prejudice. Respondents were more likely to feel threatened by immigrants than to withhold positive emotions from them. As a remedy, social connectedness in nonpolitical groups was associated with diminished blatant prejudice and lower levels of global prejudice, a measure that includes both subtle and blatant components. Findings suggest that feeling connected with different people remotely can improve attitudes toward racial and ethnic diversity, helping individuals feel less threatened by immigrants and less prejudiced overall.
{"title":"Anything but Politics: Connectedness in Networked Social Groups for Addressing Prejudice","authors":"Brandon C. Bouchillon","doi":"10.1177/08944393251320059","DOIUrl":"https://doi.org/10.1177/08944393251320059","url":null,"abstract":"Research indicates that prejudice has been growing in America. Citizens feel increasingly threatened by immigrants, and hate crimes against immigrant groups have risen. Declining interpersonal contact has also made it more difficult to address prejudice directly. This study examines whether nonpolitical social media groups can foster connections that reduce prejudice. These groups allow users to connect on the basis of shared interests, enabling diverse individuals to form close relationships which may improve attitudes toward immigrants. Using a national web survey matched to U.S. Census percentages for sex, race, ethnicity, age, and region of residence ( N = 1500), along with a two-wave panel conducted over six weeks ( N = 752), results indicate that blatant prejudice is more prevalent than subtle prejudice. Respondents were more likely to feel threatened by immigrants than to withhold positive emotions from them. As a remedy, social connectedness in nonpolitical groups was associated with diminished blatant prejudice and lower levels of global prejudice, a measure that includes both subtle and blatant components. Findings suggest that feeling connected with different people remotely can improve attitudes toward racial and ethnic diversity, helping individuals feel less threatened by immigrants and less prejudiced overall.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"22 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143485778","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 : 2025-02-12DOI: 10.1177/08944393251320063
Davide Tosi, Marco Chiappa, Dario Pizzul
As the application of artificial intelligence in various domains and sectors grows, politics—especially political communication—is no exception. However, academic considerations on the topic remain limited, partly due to its novelty. To contribute to the ongoing discussions at the intersection of AI and political campaigns, this research report presents the development and use of an AI chatbot employed by an Italian candidate during the 2024 European Parliament elections. The aim of this work is to engage with the technical aspects of the tool’s development and implementation by outlining the challenges and strategies involved in creating an AI chatbot that supports a political campaign using OpenAI APIs. Furthermore, this report offers reflections on the role of AI in politics and communication, focusing on the concepts of intermediation and participation, also addressing issues of compliance and trustworthiness of these new AI tools.
{"title":"AI Chatbots in Political Campaigns: A Practical Experience in the EU’s 2024 Parliament Elections","authors":"Davide Tosi, Marco Chiappa, Dario Pizzul","doi":"10.1177/08944393251320063","DOIUrl":"https://doi.org/10.1177/08944393251320063","url":null,"abstract":"As the application of artificial intelligence in various domains and sectors grows, politics—especially political communication—is no exception. However, academic considerations on the topic remain limited, partly due to its novelty. To contribute to the ongoing discussions at the intersection of AI and political campaigns, this research report presents the development and use of an AI chatbot employed by an Italian candidate during the 2024 European Parliament elections. The aim of this work is to engage with the technical aspects of the tool’s development and implementation by outlining the challenges and strategies involved in creating an AI chatbot that supports a political campaign using OpenAI APIs. Furthermore, this report offers reflections on the role of AI in politics and communication, focusing on the concepts of intermediation and participation, also addressing issues of compliance and trustworthiness of these new AI tools.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"15 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143393448","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 : 2025-02-07DOI: 10.1177/08944393251319740
Mridha Md. Shiblee Noman, Md. Sayeed Al-Zaman
The intersection of politics and religion in India has gained significant scholarly attention, particularly since the Bharatiya Janata Party’s (BJP) rise to power in 2014. The increasing impact of social media on Indian politics has intensified this concern. However, it is yet to be fully explored how social media was used for religiopolitical purposes during the Indian election in 2024. We computationally analyzed 3082 Facebook posts using BERTopic, word embedding, and cluster analysis to understand how politicians, political candidates, political organizations, and political parties intertwined religion and politics during the 2024 Lok Sabha election. We identified the presence of religiopolitical propaganda, primarily aimed at reviving and recreating Hindu nationalist history and targeting religious minorities, mainly Muslims. The major topics of the posts included ideological legacy, political landscape, party and leadership, celebrations, crime and justice, local politics and governance, politicized demographic trends, public engagements, spiritual and philosophical themes, and the misrepresented reservation issue. The interconnectedness of these issues suggests that the BJP and its allies concentrated on religious matters, from Hindu–Muslim debates to reservations for Muslims and the inauguration of Hindu temples. Data from non-political entities, such as influencers, as well as cross-platform analysis from Twitter and YouTube, can extend and enrich these insights.
{"title":"The Use of Religion Online by Indian Political Entities During the 2024 Lok Sabha Election: Religiopolitical Propaganda on Social Media?","authors":"Mridha Md. Shiblee Noman, Md. Sayeed Al-Zaman","doi":"10.1177/08944393251319740","DOIUrl":"https://doi.org/10.1177/08944393251319740","url":null,"abstract":"The intersection of politics and religion in India has gained significant scholarly attention, particularly since the Bharatiya Janata Party’s (BJP) rise to power in 2014. The increasing impact of social media on Indian politics has intensified this concern. However, it is yet to be fully explored how social media was used for religiopolitical purposes during the Indian election in 2024. We computationally analyzed 3082 Facebook posts using BERTopic, word embedding, and cluster analysis to understand how politicians, political candidates, political organizations, and political parties intertwined religion and politics during the 2024 Lok Sabha election. We identified the presence of religiopolitical propaganda, primarily aimed at reviving and recreating Hindu nationalist history and targeting religious minorities, mainly Muslims. The major topics of the posts included ideological legacy, political landscape, party and leadership, celebrations, crime and justice, local politics and governance, politicized demographic trends, public engagements, spiritual and philosophical themes, and the misrepresented reservation issue. The interconnectedness of these issues suggests that the BJP and its allies concentrated on religious matters, from Hindu–Muslim debates to reservations for Muslims and the inauguration of Hindu temples. Data from non-political entities, such as influencers, as well as cross-platform analysis from Twitter and YouTube, can extend and enrich these insights.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"21 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143367358","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 : 2025-01-30DOI: 10.1177/08944393251315915
Maya Kagan, Uzi Ben-Shalom, Michal Mahat-Shamir
Social media has become an integral part of daily life, shaping behaviors, self-perception, and emotional well-being. However, its addictive use raises concerns about its potential to aggravate psychological challenges, particularly in the context of societal expectations of masculinity. The current report presents a study exploring the pathways through which social media addiction contributes to masculine depression, specifically examining the roles of physical appearance comparison, self-esteem, and emotional control among men. By investigating these relationships, it aims to provide insights into the psychological consequences of social media addiction for men. Structured questionnaires were administered to 849 Israeli men aged 18 and older. Employing a moderated sequential mediation model with social media addiction as the independent variable, physical appearance comparison and self-esteem as mediators, and masculine depression as the dependent variable, this study also investigates emotional control as a moderator in the associations between social media addiction, physical appearance comparison, self-esteem, and masculine depression. The analysis, conducted using model 89 PROCESS v4.2 macro, reveals that conforming to the masculine norm of emotional control intensifies men’s vulnerability to distress resulting from maladaptive behaviors such as social media addiction, which can lead to masculine depression. Furthermore, addiction to social media can trigger masculine depression via psychosocial factors such as physical appearance comparison and low self-esteem, which have yet to be explored in the context of masculine depression. These findings underscore the importance of targeted interventions that address the societal pressures of masculinity and the psychological repercussions of excessive social media use among men. They also emphasize the necessity of raising awareness about these issues among both the public and therapists.
社交媒体已经成为日常生活中不可或缺的一部分，塑造了人们的行为、自我认知和情感健康。然而，它的成瘾性使用引起了人们对它可能加剧心理挑战的担忧，特别是在社会对男子气概的期望的背景下。目前的报告提出了一项研究，探索社交媒体成瘾导致男性抑郁的途径，特别是研究了男性的外表比较，自尊和情绪控制的作用。通过调查这些关系，该研究旨在深入了解社交媒体成瘾对男性的心理影响。对849名18岁及以上的以色列男性进行了结构化问卷调查。采用以社交媒体成瘾为自变量，外表比较和自尊为中介变量，男性抑郁为因变量的有调节序列中介模型，探讨情绪控制在社交媒体成瘾、外表比较、自尊和男性抑郁之间的调节作用。使用89 PROCESS v4.2模型进行的分析显示，符合男性的情绪控制规范会加剧男性对社交媒体成瘾等适应不良行为导致的痛苦的脆弱性，从而导致男性抑郁症。此外，社交媒体成瘾可以通过外表比较和自卑等心理社会因素引发男性抑郁症，这些因素尚未在男性抑郁症的背景下进行探讨。这些发现强调了有针对性的干预措施的重要性，以解决男性气概的社会压力和男性过度使用社交媒体的心理影响。他们还强调了提高公众和治疗师对这些问题的认识的必要性。
{"title":"The Role of Physical Appearance Comparison, Self-Esteem, and Emotional Control in the Association Between Social Media Addiction and Masculine Depression","authors":"Maya Kagan, Uzi Ben-Shalom, Michal Mahat-Shamir","doi":"10.1177/08944393251315915","DOIUrl":"https://doi.org/10.1177/08944393251315915","url":null,"abstract":"Social media has become an integral part of daily life, shaping behaviors, self-perception, and emotional well-being. However, its addictive use raises concerns about its potential to aggravate psychological challenges, particularly in the context of societal expectations of masculinity. The current report presents a study exploring the pathways through which social media addiction contributes to masculine depression, specifically examining the roles of physical appearance comparison, self-esteem, and emotional control among men. By investigating these relationships, it aims to provide insights into the psychological consequences of social media addiction for men. Structured questionnaires were administered to 849 Israeli men aged 18 and older. Employing a moderated sequential mediation model with social media addiction as the independent variable, physical appearance comparison and self-esteem as mediators, and masculine depression as the dependent variable, this study also investigates emotional control as a moderator in the associations between social media addiction, physical appearance comparison, self-esteem, and masculine depression. The analysis, conducted using model 89 PROCESS v4.2 macro, reveals that conforming to the masculine norm of emotional control intensifies men’s vulnerability to distress resulting from maladaptive behaviors such as social media addiction, which can lead to masculine depression. Furthermore, addiction to social media can trigger masculine depression via psychosocial factors such as physical appearance comparison and low self-esteem, which have yet to be explored in the context of masculine depression. These findings underscore the importance of targeted interventions that address the societal pressures of masculinity and the psychological repercussions of excessive social media use among men. They also emphasize the necessity of raising awareness about these issues among both the public and therapists.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"122 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143071509","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：