Social Science Computer Review最新文献_第6页

Explicating Trust-building Factors Impacting the Use of e-government Services 阐释影响电子政务服务使用的信任建设因素

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2023-12-18 DOI: 10.1177/08944393231220757

Suha AlAwadhi, Husain Alansari, Ahmad R. Alsaber

{"title":"Explicating Trust-building Factors Impacting the Use of e-government Services","authors":"Suha AlAwadhi, Husain Alansari, Ahmad R. Alsaber","doi":"10.1177/08944393231220757","DOIUrl":"https://doi.org/10.1177/08944393231220757","url":null,"abstract":"This study investigates the users’ perception of trust-building factors influencing the use of e-government services and information, by integrating constructs identified in the technology acceptance model (TAM) with information systems (IS) success and trust models. Data was collected using a questionnaire targeted towards users of e-government services in Kuwait. The partial least squares structural equation modeling method was used to analyze 717 valid questionnaire responses. The results indicate that information quality and design (IQD) and perceived ease of use (PEU) influence individuals’ trust in e-government (TEG), thereby affecting their behavioral intentions (BI). Furthermore, the results indicate an average level of the users’ satisfaction and significant differences in how gender and nationality are associated with the overall satisfaction of e-government services users. The proposed framework contributes to extending models by integrating IQD (a modified construct of the IS model) and PEU (a construct of the TAM) as trust-related factors that provide better insights into the driving forces of BI and should be considered when designing and developing e-government services. Additionally, the study provides a deeper understanding of the challenges that could hinder the use of e-government systems.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138995380","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}

引用次数: 0

Sex Sells Terrorism: How Sexual Appeals in Fringe Online Communities Contribute to Self-Radicalization 性出卖恐怖主义：边缘网络社区中的性诉求如何助长自我激进化

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2023-12-07 DOI: 10.1177/08944393231220490

Brian C. Britt

引用次数: 0

Social Grooming on Social Media and Older Adults’ Life Satisfaction: Testing a Moderated Mediation Model 社交媒体上的社交疏导与老年人的生活满意度：测试调节中介模型

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2023-12-06 DOI: 10.1177/08944393231220487

Piper Liping Liu, T. E. D. Yeo

{"title":"Social Grooming on Social Media and Older Adults’ Life Satisfaction: Testing a Moderated Mediation Model","authors":"Piper Liping Liu, T. E. D. Yeo","doi":"10.1177/08944393231220487","DOIUrl":"https://doi.org/10.1177/08944393231220487","url":null,"abstract":"Despite the growing prevalence of social media usage among older adults, the impact for their well-being remains unclear. This study investigates the impact of social grooming on social media (SGSM) on the life satisfaction of a representative sample ( N = 591) of older adults (aged 55 and above) in Taiwan. Using an indirect effects paradigm, the study examines the mediation mechanisms of bridging social capital and perceived social support in the relationship between SGSM and life satisfaction. Additionally, the moderating effect of social network size (SNS) is assessed. The results indicate that bridging social capital and social support fully and sequentially mediate the influence of SGSM on older adults’ life satisfaction. Furthermore, SNS is identified as a significant moderator in this sequential mediating effect. These findings contribute to the existing literature on social media use and highlight the importance of understanding the impact of SGSM on life satisfaction and other psychological outcomes for older adults. The results also emphasize the need to consider the unique characteristics and specific needs of older adults, and to promote and assist them in effectively using social media to expand their social networks and acquire social support, which are crucial for their life satisfaction.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138597710","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}

引用次数: 0

A Two-Step Method for Classifying Political Partisanship Using Deep Learning Models 利用深度学习模型划分政治党派的两步法

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2023-12-06 DOI: 10.1177/08944393231219685

Lingshu Hu

{"title":"A Two-Step Method for Classifying Political Partisanship Using Deep Learning Models","authors":"Lingshu Hu","doi":"10.1177/08944393231219685","DOIUrl":"https://doi.org/10.1177/08944393231219685","url":null,"abstract":"Political partisanship constitutes a pivotal group identity that significantly influences individuals’ voting behaviors and shapes their ideological and cultural perspectives. While traditional surveys and experimental studies can directly capture political identity by asking the participants, this task has become intricate when employing digital trace data sourced from social media. Previous classification methods, attempting to infer political identity from users’ networks or textual content, suffered from limited efficiency or generalizability. In response, this study introduces a two-step method that utilizes deep learning models to enhance classification efficiency, generalizability, and interpretability. In the first step, two deep learning models, trained on 2.5 million tweets from 825 Congressional politicians in the U.S., achieved accuracy rates of 87.71% and 89.54%, respectively, in detecting politicians’ partisanships based on their individual tweets. Subsequently, in the second step, by employing a simple machine learning model that leverages the aggregated predicted values derived from the first-step models, accuracy rates of 94.92% and 96.61% were attained for identifying non-politician users’ political identities based off their 50 and 200 tweets, respectively. In addition, an attention mechanism was integrated into the deep learning model to assess the contribution of each word in the classification process.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138596600","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}

引用次数: 0

Potential Pitfalls With Automatic Sentiment Analysis: The Example of Queerphobic Bias. 自动情绪分析的潜在陷阱:同性恋恐惧症偏见的例子

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2023-12-01 Epub Date: 2023-02-02 DOI: 10.1177/08944393231152946

Eddie L Ungless, Björn Ross, Vaishak Belle

引用次数: 2

Bridging Qualitative Data Silos: The Potential of Reusing Codings Through Machine Learning Based Cross-Study Code Linking 桥接定性数据孤岛:通过基于机器学习的交叉研究代码链接重用编码的潜力

2区社会学

Social Science Computer Review Pub Date : 2023-11-13 DOI: 10.1177/08944393231215459

Sergej Wildemann, Claudia Niederée, Erick Elejalde

{"title":"Bridging Qualitative Data Silos: The Potential of Reusing Codings Through Machine Learning Based Cross-Study Code Linking","authors":"Sergej Wildemann, Claudia Niederée, Erick Elejalde","doi":"10.1177/08944393231215459","DOIUrl":"https://doi.org/10.1177/08944393231215459","url":null,"abstract":"For qualitative data analysis (QDA), researchers assign codes to text segments to arrange the information into topics or concepts. These annotations facilitate information retrieval and the identification of emerging patterns in unstructured data. However, this metadata is typically not published or reused after the research. Subsequent studies with similar research questions require a new definition of codes and do not benefit from other analysts’ experience. Machine learning (ML) based classification seeded with such data remains a challenging task due to the ambiguity of code definitions and the inherent subjectivity of the exercise. Previous attempts to support QDA using ML rely on linear models and only examined individual datasets that were either smaller or coded specifically for this purpose. However, we show that modern approaches effectively capture at least part of the codes’ semantics and may generalize to multiple studies. We analyze the performance of multiple classifiers across three large real-world datasets. Furthermore, we propose an ML-based approach to identify semantic relations of codes in different studies to show thematic faceting, enhance retrieval of related content, or bootstrap the coding process. These are encouraging results that suggest how analysts might benefit from prior interpretation efforts, potentially yielding new insights into qualitative data.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136346256","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}

引用次数: 0

Exploring Customer Citizenship Behavior in Social Commerce From the Parasocial Perspective 从准社会视角探讨社交商务中的顾客公民行为

2区社会学

Social Science Computer Review Pub Date : 2023-11-10 DOI: 10.1177/08944393231214026

Jinqi Men, Xiabing Zheng, Feifei Shan, Xiao Shi, Feng Yang

引用次数: 0

They’re Coming for You! How Perceptions of Automation Affect Public Support for Universal Basic Income 他们来找你了!对自动化的认知如何影响公众对全民基本收入的支持

2区社会学

Social Science Computer Review Pub Date : 2023-11-08 DOI: 10.1177/08944393231212252

Kathryn Haglin, Soren Jordan, Grant Ferguson

引用次数: 0

Media Representations of Healthcare Robotics in Norway 2000-2020: A Topic Modeling Approach 挪威2000-2020年医疗机器人的媒体表示:主题建模方法

2区社会学

Social Science Computer Review Pub Date : 2023-11-07 DOI: 10.1177/08944393231212251

Mads Solberg, Ralf Kirchhoff

{"title":"Media Representations of Healthcare Robotics in Norway 2000-2020: A Topic Modeling Approach","authors":"Mads Solberg, Ralf Kirchhoff","doi":"10.1177/08944393231212251","DOIUrl":"https://doi.org/10.1177/08944393231212251","url":null,"abstract":"Robots are projected to affect healthcare services in significant, but unpredictable, ways. Many believe robots will add value to future healthcare, but their arrival has triggered controversy. Debates revolve around how robotics will impact healthcare provision, their effects on the future of labor and caregiver–patient relationships, and ethical dilemmas associated with autonomous machines. This study investigates media representations of healthcare robotics in Norway over a twenty-year period, using a mixed-methods design. Media representations affect public opinion in multiple ways. By assembling and presenting information through stories, they not only set the agenda by broadcasting values, experiences, and expectations about new technologies, but also frame and prime specific understandings of issues. First, we employ an inductive text-mining approach known as “topic modeling,” a computational method for eliciting abstract semantic structures from large text corpora. Using Non-Negative Matrix Factorization, we implement a topic model of manifest content from 752 articles, published in Norwegian print media between 1.1.2000 and 2.10.2020, sampled from a comprehensive database for news media (Atekst, Retriever). We complement this computational lens with a more fine-grained, qualitative analysis of content in exemplary texts sampled from each topic. Here, we identify prominent “frames,” discursive cues for interpreting how various stakeholders talk about healthcare robotics as a contested domain of policy and practice in a comprehensive welfare state. We also highlight some benefits of this approach for analyzing media discourse and stakeholder perspectives on controversial technologies.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135432832","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}

引用次数: 0

Measuring Hate: Does a Definition Affect Self-Reported Levels of Perpetration and Exposure to Online Hate in Surveys? 测量仇恨:一个定义会影响自我报告的犯罪水平和调查中的在线仇恨暴露吗?

2区社会学

Social Science Computer Review Pub Date : 2023-11-01 DOI: 10.1177/08944393231211270

James Hawdon, Ashley Reichelmann, Matthew Costello, Vicente J. Llorent, Pekka Räsänen, Izabela Zych, Atte Oksanen, Catherine Blaya

{"title":"Measuring Hate: Does a Definition Affect Self-Reported Levels of Perpetration and Exposure to Online Hate in Surveys?","authors":"James Hawdon, Ashley Reichelmann, Matthew Costello, Vicente J. Llorent, Pekka Räsänen, Izabela Zych, Atte Oksanen, Catherine Blaya","doi":"10.1177/08944393231211270","DOIUrl":"https://doi.org/10.1177/08944393231211270","url":null,"abstract":"The purpose of this research is to test the validity of commonly used measures of exposure to and production of online extremism. Specifically, we investigate if a definition of hate influences survey responses about the production of and exposure to online hate. To explore the effects of a definition, we used a split experimental design on a sample of 18 to 25-year-old Americans where half of the respondents were exposed to the European Union’s definition of hate speech and the other half were not. Then, all respondents completed a survey with commonly used items measuring exposure to and perpetration of online hate. The results reveal that providing a definition affects self-reported levels of exposure and perpetration, but the effects are dependent on race. The findings provide evidence that survey responses about online hate may be conditioned by social desirability and framing biases. The findings that group differences exist in how questions about hate are interpreted when definitions of it are not provided mean we must be careful when using measures that try to capture exposure to and the production of hate. While more research is needed, we recommend providing a clear, unambiguous definition when using surveys to measure online hate.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135271566","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}

引用次数: 0