ObjectiveUsers of social media platforms such as Facebook, Instagram, and Twitter can view and share their daily life events through text, photographs, or videos. These platforms receive many sarcastic posts daily because there were fewer limits on what could be posted. The presence of multiple languages and media types in a single post makes it harder to identify sarcastic messages on the current platform than on posts written solely in English.MethodsThis study provides both the theory and solutions about sarcastic post detection on social platforms. Hindi–English code‐mixed data were used to train and test the automated models for sarcasm detection. The models in this study were constructed using traditional machine learning, deep neural networks, LSTM (long short‐term memory), CNN (convolutional neural network), and the combinations of BERT (Bidirectional Encoder Representations from Transformers) with LSTM.ResultsThe experimental results confirm that in the Hindi–English code‐mixed data set, the CNN, LSTM, and BERT‐LSTM ensemble perform best for sarcasm detection. The proposed model achieved an accuracy of 96.29 percent and outperformed by 2.29 percent compared to the existing models.ConclusionThe performance of the proposed system strengthens the code‐mixed sarcastic post detection on social platforms. The model will help filter not only English but also Hindi‐English code‐mixed sarcastic posts on social platforms.
{"title":"An advanced learning approach for detecting sarcasm in social media posts: Theory and solutions","authors":"Pradeep Kumar Roy","doi":"10.1111/ssqu.13442","DOIUrl":"https://doi.org/10.1111/ssqu.13442","url":null,"abstract":"ObjectiveUsers of social media platforms such as Facebook, Instagram, and Twitter can view and share their daily life events through text, photographs, or videos. These platforms receive many sarcastic posts daily because there were fewer limits on what could be posted. The presence of multiple languages and media types in a single post makes it harder to identify sarcastic messages on the current platform than on posts written solely in English.MethodsThis study provides both the theory and solutions about sarcastic post detection on social platforms. Hindi–English code‐mixed data were used to train and test the automated models for sarcasm detection. The models in this study were constructed using traditional machine learning, deep neural networks, LSTM (long short‐term memory), CNN (convolutional neural network), and the combinations of BERT (Bidirectional Encoder Representations from Transformers) with LSTM.ResultsThe experimental results confirm that in the Hindi–English code‐mixed data set, the CNN, LSTM, and BERT‐LSTM ensemble perform best for sarcasm detection. The proposed model achieved an accuracy of 96.29 percent and outperformed by 2.29 percent compared to the existing models.ConclusionThe performance of the proposed system strengthens the code‐mixed sarcastic post detection on social platforms. The model will help filter not only English but also Hindi‐English code‐mixed sarcastic posts on social platforms.","PeriodicalId":48253,"journal":{"name":"Social Science Quarterly","volume":"8 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142261577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ObjectiveCongressional candidates use digital platforms to bolster and define their political reputation, and political stalemates over inflation, reproductive rights, and the lasting impact of Trump politics are fueling candidates’ emotionally charged rhetoric on Twitter, especially for women. Against the backdrop of President Donald Trump's presidency and the #MeToo movement, previous research has shown that women running for Congress are leading with angry rhetoric on Twitter. In this article, we ask whether anger is a persistent feature of women's digital appeals on Twitter over time.MethodUsing a data set of tweets by candidates for the U.S. House from 2016 to 2022, we highlight the escalating anger in the emotional appeals candidates make on Twitter and the resiliency of angry rhetoric as a modern feature of political Twitter.ResultsWe find that women, most notably Democratic candidates, are more likely to convey angry emotions on Twitter, not only matching male colleagues but defying gendered social stereotypes to turn frustration into a valuable political asset. Across the four last congressional elections, women have averaged more angry words in their digital appeals, with that anger as a consistent facet of how women engage online. Women are leaning into angry emotional appeals and adopting a negative appeal in their digital engagement that highlights their policy and political frustrations for voters.
{"title":"Not ready to make nice: Congressional candidates’ emotional appeals on Twitter","authors":"Annelise Russell, Heather K. Evans, Bryan Gervais","doi":"10.1111/ssqu.13439","DOIUrl":"https://doi.org/10.1111/ssqu.13439","url":null,"abstract":"ObjectiveCongressional candidates use digital platforms to bolster and define their political reputation, and political stalemates over inflation, reproductive rights, and the lasting impact of Trump politics are fueling candidates’ emotionally charged rhetoric on Twitter, especially for women. Against the backdrop of President Donald Trump's presidency and the #MeToo movement, previous research has shown that women running for Congress are leading with angry rhetoric on Twitter. In this article, we ask whether anger is a persistent feature of women's digital appeals on Twitter over time.MethodUsing a data set of tweets by candidates for the U.S. House from 2016 to 2022, we highlight the escalating anger in the emotional appeals candidates make on Twitter and the resiliency of angry rhetoric as a modern feature of political Twitter.ResultsWe find that women, most notably Democratic candidates, are more likely to convey angry emotions on Twitter, not only matching male colleagues but defying gendered social stereotypes to turn frustration into a valuable political asset. Across the four last congressional elections, women have averaged more angry words in their digital appeals, with that anger as a consistent facet of how women engage online. Women are leaning into angry emotional appeals and adopting a negative appeal in their digital engagement that highlights their policy and political frustrations for voters.","PeriodicalId":48253,"journal":{"name":"Social Science Quarterly","volume":"21 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142261579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ObjectiveAn extensive literature examines the prevalence of conspiracy theories and the factors that determine why some people believe them. Conspiracy theories are only one example of baseless beliefs, which we define as beliefs that are not epistemically warranted by the available evidence. The goals of this research were to determine if there are discrete domains of baseless beliefs and to identify the psychological and cognitive factors most closely associated with each type.MethodsWe surveyed 435 U.S. adults about their baseless beliefs and measured an extensive set of cognitive, epistemological, and personal characteristics.ResultsFour distinct domains of baseless belief were discovered, which we label conservative controversies, classic coverups, magical thoughts, and pseudoscience. The data suggest the confidence people have in these beliefs differs across domains and reveal clear differences in the cognitive, epistemological, and personality factors predicting belief in each domain.ConclusionBaseless beliefs encompass a number of distinct domains, and the psychological dynamics underlying belief acquisition vary across these domains. This finding suggests caution in generalizing from studies examining only one domain. The prominent role of conservatism documented in the literature on conspiracy theories, for example, is weaker or not present at all in other domains.
{"title":"Domains of baseless belief and the characteristics of believers","authors":"Douglas D. Roscoe, Amy M. Shapiro, Brian Ayotte","doi":"10.1111/ssqu.13448","DOIUrl":"https://doi.org/10.1111/ssqu.13448","url":null,"abstract":"ObjectiveAn extensive literature examines the prevalence of conspiracy theories and the factors that determine why some people believe them. Conspiracy theories are only one example of <jats:italic>baseless beliefs</jats:italic>, which we define as beliefs that are not epistemically warranted by the available evidence. The goals of this research were to determine if there are discrete domains of baseless beliefs and to identify the psychological and cognitive factors most closely associated with each type.MethodsWe surveyed 435 U.S. adults about their baseless beliefs and measured an extensive set of cognitive, epistemological, and personal characteristics.ResultsFour distinct domains of baseless belief were discovered, which we label conservative controversies, classic coverups, magical thoughts, and pseudoscience. The data suggest the confidence people have in these beliefs differs across domains and reveal clear differences in the cognitive, epistemological, and personality factors predicting belief in each domain.ConclusionBaseless beliefs encompass a number of distinct domains, and the psychological dynamics underlying belief acquisition vary across these domains. This finding suggests caution in generalizing from studies examining only one domain. The prominent role of conservatism documented in the literature on conspiracy theories, for example, is weaker or not present at all in other domains.","PeriodicalId":48253,"journal":{"name":"Social Science Quarterly","volume":"77 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142261575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kristen N. Jozkowski, Brandon L. Crawford, Amelia Hawbaker, Erik Parker, Lilian Golzarri Arroyo, Ronna C. Turner
ObjectiveNational public opinion polls and surveys use different questions from one another to assess people's abortion attitudes. We included commonly asked abortion attitude items on a single survey to examine people's attitudes toward abortion legality and abortion restriction to create profiles of people which we then compared across state groups. Concurrently assessing attitudes toward both abortion legality and restrictions is important given the changing abortion legislative climate in the United States.MethodWe administered an online survey to U.S. adults (n = 919) via Ipsos probability panel and used latent class analysis to identify classes of participants. Then, we used multinominal logistic regression to make state‐level comparisons.ResultsWe identified three classes: (1) 35.0 percent—abortion should be illegal/more restricted, (2) 35.1 percent—abortion should be legal/laws should reflect the status quo, and (3) 29.9 percent—abortion should be legal/more available. Trigger‐law states comprise the largest proportion of people who think abortion should be illegal/more restricted, whereas states without trigger laws comprise similar proportions of people from all three classes.ConclusionConcurrently measuring whether people believe abortion should be legal and the extent it should be restricted can provide a more comprehensive understanding of people's attitudes and demonstrates important state‐level nuances in attitudes.
{"title":"Attitudes toward abortion legality and abortion regulation: Insights from a nationally representative study","authors":"Kristen N. Jozkowski, Brandon L. Crawford, Amelia Hawbaker, Erik Parker, Lilian Golzarri Arroyo, Ronna C. Turner","doi":"10.1111/ssqu.13443","DOIUrl":"https://doi.org/10.1111/ssqu.13443","url":null,"abstract":"ObjectiveNational public opinion polls and surveys use different questions from one another to assess people's abortion attitudes. We included commonly asked abortion attitude items on a single survey to examine people's attitudes toward abortion legality and abortion restriction to create profiles of people which we then compared across state groups. Concurrently assessing attitudes toward both abortion legality and restrictions is important given the changing abortion legislative climate in the United States.MethodWe administered an online survey to U.S. adults (<jats:italic>n</jats:italic> = 919) via Ipsos probability panel and used latent class analysis to identify classes of participants. Then, we used multinominal logistic regression to make state‐level comparisons.ResultsWe identified three classes: (1) 35.0 percent—abortion should be illegal/more restricted, (2) 35.1 percent—abortion should be legal/laws should reflect the status quo, and (3) 29.9 percent—abortion should be legal/more available. Trigger‐law states comprise the largest proportion of people who think abortion should be illegal/more restricted, whereas states without trigger laws comprise similar proportions of people from all three classes.ConclusionConcurrently measuring whether people believe abortion should be legal and the extent it should be restricted can provide a more comprehensive understanding of people's attitudes and demonstrates important state‐level nuances in attitudes.","PeriodicalId":48253,"journal":{"name":"Social Science Quarterly","volume":"30 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142261576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ObjectiveMany governments aim for transparency for accountability. Transparency and its processes contribute to governing climate. The transparency agenda focuses on sharing records to inform the public. In the United States, accessible records also add to decision‐making processes since records are useful to contest decisions. Few people put together the two kinds of transparency, sharing and challenging. Analyzing both is critical as calls for acting on climate‐related disasters grow.MethodIn the United States, the Federal Emergency Management Agency (FEMA) shares records. The Freedom of Information Act (FOIA) is one route to access FEMA's records. To assess transparency, I coded FEMA's 2019 FOIA log for requester and record requested. Years of damaging, notable disasters preceded 2019, but 2019 precedes pandemic disruptions.ResultRequesters can make requests likely to be useful instrumentally, concerning assistance and insurance. Journalists and scholars request records useful to conceptualizing governing disaster to include both individual political officials and aggregate bureaucratic policy. Instrumental requests dominate, as they do for other agencies.ConclusionThis article answers the call in recent studies of transparency, policy, and of disaster governance to track how policies embed power. Assessing record requests contributes to understanding the accountability in freedom of information.
{"title":"Climate‐related disasters and transparency: Records and the United States Federal Emergency Management Agency","authors":"Susan M. Sterett","doi":"10.1111/ssqu.13441","DOIUrl":"https://doi.org/10.1111/ssqu.13441","url":null,"abstract":"ObjectiveMany governments aim for transparency for accountability. Transparency and its processes contribute to governing climate. The transparency agenda focuses on sharing records to inform the public. In the United States, accessible records also add to decision‐making processes since records are useful to contest decisions. Few people put together the two kinds of transparency, sharing and challenging. Analyzing both is critical as calls for acting on climate‐related disasters grow.MethodIn the United States, the Federal Emergency Management Agency (FEMA) shares records. The Freedom of Information Act (FOIA) is one route to access FEMA's records. To assess transparency, I coded FEMA's 2019 FOIA log for requester and record requested. Years of damaging, notable disasters preceded 2019, but 2019 precedes pandemic disruptions.ResultRequesters can make requests likely to be useful instrumentally, concerning assistance and insurance. Journalists and scholars request records useful to conceptualizing governing disaster to include both individual political officials and aggregate bureaucratic policy. Instrumental requests dominate, as they do for other agencies.ConclusionThis article answers the call in recent studies of transparency, policy, and of disaster governance to track how policies embed power. Assessing record requests contributes to understanding the accountability in freedom of information.","PeriodicalId":48253,"journal":{"name":"Social Science Quarterly","volume":"24 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142261578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Richard C. Sadler, Thomas W. Wojciechowski, Eileen Hayes
ObjectiveVoter purges can protect election integrity by ensuring deceased or moved individuals are removed from election rolls. But they have been used to diminish voting power of marginalized groups, often by anti‐majoritarian forces seeking to undemocratically retain power. Little research has examined “who gets purged?” at the state level, especially with respect to local‐level differences.MethodsWe leverage Michigan's voter purge database from 2014 to 2018. Records are geocoded to their exact address, and a range of spatial correlates are identified to answer the above question. We then used generalized structural equation modeling to incorporate patterns of mobility and mortality.ResultsInitial results showed that more Democratic leaning areas, denser/more urban areas, and areas with more Black residents had higher purge rates. Notably, while these mediation effects were significant, racial composition and median income (i.e. more black and poorer communities) remained a significant factor in voter purge rates. These results suggest a potentially troublesome underlying element in Michigan's pattern of voter purges. We suggest this is an important first step in future research in other states and with subsequent databases, which can help strengthen the case that purges may be being used to uphold discriminatory and anti‐majoritarian goals.
{"title":"Spatial and statistical predictors of voter purge rates in Michigan","authors":"Richard C. Sadler, Thomas W. Wojciechowski, Eileen Hayes","doi":"10.1111/ssqu.13447","DOIUrl":"https://doi.org/10.1111/ssqu.13447","url":null,"abstract":"ObjectiveVoter purges can protect election integrity by ensuring deceased or moved individuals are removed from election rolls. But they have been used to diminish voting power of marginalized groups, often by anti‐majoritarian forces seeking to undemocratically retain power. Little research has examined “who gets purged?” at the state level, especially with respect to local‐level differences.MethodsWe leverage Michigan's voter purge database from 2014 to 2018. Records are geocoded to their exact address, and a range of spatial correlates are identified to answer the above question. We then used generalized structural equation modeling to incorporate patterns of mobility and mortality.ResultsInitial results showed that more Democratic leaning areas, denser/more urban areas, and areas with more Black residents had higher purge rates. Notably, while these mediation effects were significant, racial composition and median income (i.e. more black and poorer communities) remained a significant factor in voter purge rates. These results suggest a potentially troublesome underlying element in Michigan's pattern of voter purges. We suggest this is an important first step in future research in other states and with subsequent databases, which can help strengthen the case that purges may be being used to uphold discriminatory and anti‐majoritarian goals.","PeriodicalId":48253,"journal":{"name":"Social Science Quarterly","volume":"25 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142196193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Martin K. Mayer, John C. Morris, Madeleine W. McNamara, Xiaodan Zhang
ObjectivesWith the rejuvenated emphasis on nonpoint pollution under the Water Quality Act (WQA) of 1987, Environmental Protection Agency (EPA) began to face an onslaught of lawsuits designed to pressure the EPA to enforce the requirements of Section 319 of the WQA to address nonpoint pollution. Known as Total Maximum Daily Load (TMDL) agreements, the purpose of these plans was to limit the amount of polluted runoff reaching a state's waterways. While some states took a proactive stance on these plans, other states resisted the implementation of Section 319. This article seeks to understand state choices in the development and implementation of TMDL agreements.MethodsUtilizing a data set spanning state‐level data from 2000 to 2020, we test a novel cross‐sectional time series model employing the number agreements entered into by a state as the dependent variable.ResultsWe find that both political and need explanations are generally supported, while policy need explanations are somewhat more promising.ConclusionsTaken together, the models offer several insights into state choices around TMDL creation. The political model is the weakest, suggesting that TMDLs are not overtly political. Policy needs seem to play a more critical role in the preponderance of TMDL agreements than partisan politics.
{"title":"Explaining state efforts to create Total Maximum Daily Load (TMDL) agreements","authors":"Martin K. Mayer, John C. Morris, Madeleine W. McNamara, Xiaodan Zhang","doi":"10.1111/ssqu.13444","DOIUrl":"https://doi.org/10.1111/ssqu.13444","url":null,"abstract":"ObjectivesWith the rejuvenated emphasis on nonpoint pollution under the Water Quality Act (WQA) of 1987, Environmental Protection Agency (EPA) began to face an onslaught of lawsuits designed to pressure the EPA to enforce the requirements of Section 319 of the WQA to address nonpoint pollution. Known as Total Maximum Daily Load (TMDL) agreements, the purpose of these plans was to limit the amount of polluted runoff reaching a state's waterways. While some states took a proactive stance on these plans, other states resisted the implementation of Section 319. This article seeks to understand state choices in the development and implementation of TMDL agreements.MethodsUtilizing a data set spanning state‐level data from 2000 to 2020, we test a novel cross‐sectional time series model employing the number agreements entered into by a state as the dependent variable.ResultsWe find that both political and need explanations are generally supported, while policy need explanations are somewhat more promising.ConclusionsTaken together, the models offer several insights into state choices around TMDL creation. The political model is the weakest, suggesting that TMDLs are not overtly political. Policy needs seem to play a more critical role in the preponderance of TMDL agreements than partisan politics.","PeriodicalId":48253,"journal":{"name":"Social Science Quarterly","volume":"1 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142196194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sara McLaughlin Mitchell, Elise Pizzi, Carly Millerd, Jeongho Choi
ObjectiveWe consider how the Peruvian government's responses to natural disaster events shaped political violence patterns from 1989 to 2020.MethodsWe gather data on government disaster response and compare the effect of positive disaster responses, such as reconstruction and regulation of domestic/international aid, and negative disaster responses, such as neglect or placing restrictions on movement near the affected areas, on violent conflict. To address the endogeneity between armed conflict and disaster responses, we estimate a structural equation model where we allow armed conflicts and disaster responses to be fully endogenous.ResultsUsing a structural equation model at the province‐year level, we show that negative disaster responses increase the risks for political violence, while positive disaster responses do not affect the risks for armed conflict. Armed conflict in turn makes negative policy responses to disasters more likely but has no effect on positive disaster responses.ConclusionsThe results suggest that poor government response to natural disasters can foster grievances and aid rebel recruitment, increasing the risks for armed conflicts.
{"title":"Does government response to natural disasters explain violence? The case of the Sendero Luminoso and conflict in Peru","authors":"Sara McLaughlin Mitchell, Elise Pizzi, Carly Millerd, Jeongho Choi","doi":"10.1111/ssqu.13438","DOIUrl":"https://doi.org/10.1111/ssqu.13438","url":null,"abstract":"ObjectiveWe consider how the Peruvian government's responses to natural disaster events shaped political violence patterns from 1989 to 2020.MethodsWe gather data on government disaster response and compare the effect of positive disaster responses, such as reconstruction and regulation of domestic/international aid, and negative disaster responses, such as neglect or placing restrictions on movement near the affected areas, on violent conflict. To address the endogeneity between armed conflict and disaster responses, we estimate a structural equation model where we allow armed conflicts and disaster responses to be fully endogenous.ResultsUsing a structural equation model at the province‐year level, we show that negative disaster responses increase the risks for political violence, while positive disaster responses do not affect the risks for armed conflict. Armed conflict in turn makes negative policy responses to disasters more likely but has no effect on positive disaster responses.ConclusionsThe results suggest that poor government response to natural disasters can foster grievances and aid rebel recruitment, increasing the risks for armed conflicts.","PeriodicalId":48253,"journal":{"name":"Social Science Quarterly","volume":"70 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142196195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ObjectiveThis study investigates whether the perceived stigma of loneliness is positively associated with the concealment of loneliness and whether this association varies by the gender of the individual and their conversation partner.MethodsUtilizing ordinal probit regression analysis on data from 1671 German survey participants with three‐way interactions, we analyze whether participants are more likely to conceal loneliness based on their perceived stigma of loneliness, their gender, and the gender of fictional, randomly assigned conversation partners.ResultsOur analysis finds that perceived stigma is positively associated with the concealment of loneliness, with this association being stronger among men compared to women. Additionally, while the influence of perceived stigma on concealment is not significant for women in same‐sex interactions, it is significantly stronger for men in same‐sex interactions.ConclusionThe interaction of gender, interviewer characteristics, and perceived stigma should be considered when designing surveys and implementing effective interventions and policies to address and destigmatize loneliness.
{"title":"Revealing loneliness: Disentangling the interaction of gender and community stigma","authors":"Alexander Langenkamp, Janosch Schobin","doi":"10.1111/ssqu.13434","DOIUrl":"https://doi.org/10.1111/ssqu.13434","url":null,"abstract":"ObjectiveThis study investigates whether the perceived stigma of loneliness is positively associated with the concealment of loneliness and whether this association varies by the gender of the individual and their conversation partner.MethodsUtilizing ordinal probit regression analysis on data from 1671 German survey participants with three‐way interactions, we analyze whether participants are more likely to conceal loneliness based on their perceived stigma of loneliness, their gender, and the gender of fictional, randomly assigned conversation partners.ResultsOur analysis finds that perceived stigma is positively associated with the concealment of loneliness, with this association being stronger among men compared to women. Additionally, while the influence of perceived stigma on concealment is not significant for women in same‐sex interactions, it is significantly stronger for men in same‐sex interactions.ConclusionThe interaction of gender, interviewer characteristics, and perceived stigma should be considered when designing surveys and implementing effective interventions and policies to address and destigmatize loneliness.","PeriodicalId":48253,"journal":{"name":"Social Science Quarterly","volume":"86 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142196196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PurposePolitical participation has been identified as a predictor of mental health. Previous research studies have reported mixed results concerning the relationship between political participation and mental health. Moreover, findings have generally been confined to the between‐individual level. The few studies that investigated within‐person associations have not examined bidirectionality. In the current study, the bidirectional relationship between political participation and mental health was investigated.MethodsData from the GESIS Panel study were used to assess the bidirectional association between political participation and mental health. The GESIS Panel study is a probability‐based panel representative of the German‐speaking population residing in Germany and aged between 18 and 70 years (M = 44.52; SD = 14.67; 52 percent female participants). Mental health was assessed using measures of depression symptoms and subjective well‐being.ResultsUsing up to nine waves of longitudinal survey data, a random‐intercept cross‐lagged panel model indicated little evidence for cross‐lagged effects from political participation to mental health or vice versa. Notwithstanding, few significant cross‐lagged paths were observed.ConclusionsOverall, the findings were not consistent with the theorized effect of political participation on mental health. Moreover, there is little evidence that mental health affects political participation.
{"title":"The reciprocal relationship between political participation and mental health in Germany: A random‐intercept cross‐lagged panel analysis","authors":"Gabriele Prati","doi":"10.1111/ssqu.13440","DOIUrl":"https://doi.org/10.1111/ssqu.13440","url":null,"abstract":"PurposePolitical participation has been identified as a predictor of mental health. Previous research studies have reported mixed results concerning the relationship between political participation and mental health. Moreover, findings have generally been confined to the between‐individual level. The few studies that investigated within‐person associations have not examined bidirectionality. In the current study, the bidirectional relationship between political participation and mental health was investigated.MethodsData from the GESIS Panel study were used to assess the bidirectional association between political participation and mental health. The GESIS Panel study is a probability‐based panel representative of the German‐speaking population residing in Germany and aged between 18 and 70 years (<jats:italic>M</jats:italic> = 44.52; SD = 14.67; 52 percent female participants). Mental health was assessed using measures of depression symptoms and subjective well‐being.ResultsUsing up to nine waves of longitudinal survey data, a random‐intercept cross‐lagged panel model indicated little evidence for cross‐lagged effects from political participation to mental health or vice versa. Notwithstanding, few significant cross‐lagged paths were observed.ConclusionsOverall, the findings were not consistent with the theorized effect of political participation on mental health. Moreover, there is little evidence that mental health affects political participation.","PeriodicalId":48253,"journal":{"name":"Social Science Quarterly","volume":"46 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142196197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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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