Social Science Computer Review最新文献_第8页

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 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Social Science Computer Review

Pub Date : 2023-11-07 DOI: 10.1177/08944393231212251

Mads Solberg, Ralf Kirchhoff

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.

预计机器人将以重大但不可预测的方式影响医疗服务。许多人认为机器人将为未来的医疗保健增添价值，但它们的到来引发了争议。辩论围绕着机器人将如何影响医疗保健服务，它们对未来劳动和护理者与患者关系的影响，以及与自主机器相关的伦理困境。本研究调查媒体代表医疗机器人在挪威超过二十年期间，使用混合方法设计。媒体以多种方式影响公众舆论。通过故事收集和呈现信息，他们不仅通过传播价值观、经验和对新技术的期望来设定议程，而且还构建和推动对问题的具体理解。首先，我们采用了一种被称为“主题建模”的归纳文本挖掘方法，这是一种从大型文本语料库中提取抽象语义结构的计算方法。使用非负矩阵分解，我们实现了从2000年1月1日至2020年10月2日期间在挪威印刷媒体上发表的752篇文章的清单内容的主题模型，这些文章从新闻媒体的综合数据库(Atekst, retriver)中采样。我们补充这个计算镜头与更细粒度，定性分析的内容在示范性文本从每个主题取样。在这里，我们确定了突出的“框架”，用于解释各种利益相关者如何将医疗机器人作为全面福利国家中有争议的政策和实践领域讨论的话语线索。我们还强调了这种方法在分析媒体话语和利益相关者对有争议技术的观点方面的一些好处。

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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 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

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

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.

本研究的目的是测试通常使用的测量网络极端主义暴露和产生的有效性。具体地说，我们调查了仇恨的定义是否会影响关于在线仇恨的产生和暴露的调查反应。为了探索定义的影响，我们对18至25岁的美国人样本进行了分裂实验设计，其中一半的受访者接触到欧盟对仇恨言论的定义，另一半则没有。然后，所有受访者都完成了一项调查，其中包括衡量网络仇恨暴露和实施的常用项目。结果表明，提供一个定义会影响自我报告的暴露和犯罪水平，但影响取决于种族。这些发现提供了证据，表明关于网络仇恨的调查反应可能受到社会期望和框架偏见的制约。研究发现，当没有提供仇恨的定义时，如何解释仇恨的问题存在群体差异，这意味着我们在使用试图捕捉仇恨暴露和产生的措施时必须谨慎。虽然需要更多的研究，但我们建议在使用调查来衡量网络仇恨时提供一个清晰、明确的定义。

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引用次数: 0

A comprehensive analysis of stroke admissions at a rural Nigerian tertiary health facility: Insights from a single-center study. 尼日利亚农村三级医疗机构卒中入院的综合分析:来自单中心研究的见解。

IF 1.4 2区社会学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Social Science Computer Review

Pub Date : 2023-10-01 Epub Date: 2023-06-24 DOI: 10.25259/JNRP_76_2023

Cyril Oshomah Erameh, Airenakho Emorinken, Blessyn Omoye Akpasubi

Objectives: This research intended to examine the demographic and clinical attributes of stroke admissions in a rural Nigerian hospital.

Materials and methods: A retrospective analysis of stroke admissions was conducted over 1 year. All necessary data were obtained from patients' records and SPSS was employed for data analysis. P < 0.05 was deemed significant.

Results: There were 52 stroke cases, accounting for 5.9% of medical admissions. The patients' mean age was 62.81 ± 12.71 years, while females constituted 51.9% of cases. Common risk factors included hypertension (76.9%), hyperlipidemia (38.5%), alcohol (26.9%), and diabetes mellitus (26.9%). Clinical manifestations included hemiparesis/plegia (84.6%), altered consciousness (63.5%), slurred speech (61.5%), cranial nerve deficit (61.5%), aphasia (42.3%), and headache (34.6%). Ischemic stroke (71.2%) predominated over hemorrhagic stroke (28.8%). The average hospitalization duration was 17.62 ± 8.91 days, and the mean onset to arrival time was 121.31 ± 136.06 h. Discharge and mortality rates were 82.7% and 13.5%, respectively. The association between stroke subtypes and mortality was significant (P = 0.001).

Conclusion: Stroke constitutes a significant portion of medical admissions in Nigeria, with ischemic stroke being more prevalent. High mortality rates underscore the urgent need to manage risk factors to prevent stroke.

目的:本研究旨在研究尼日利亚一家农村医院卒中入院的人口统计学和临床特征。材料和方法:回顾性分析1年以上卒中入院患者。所有必要的数据均从患者病历中获取，并采用SPSS软件进行数据分析。P < 0.05为差异有统计学意义。结果:卒中患者52例，占住院人数的5.9%。患者平均年龄62.81±12.71岁，女性占51.9%。常见的危险因素包括高血压(76.9%)、高脂血症(38.5%)、酒精(26.9%)和糖尿病(26.9%)。临床表现包括偏瘫/瘫痪(84.6%)、意识改变(63.5%)、言语不清(61.5%)、颅神经缺损(61.5%)、失语(42.3%)、头痛(34.6%)。缺血性中风(71.2%)高于出血性中风(28.8%)。平均住院时间为17.62±8.91 d，平均起病至到达时间为121.31±136.06 h，出院率为82.7%，死亡率为13.5%。卒中亚型与死亡率之间存在显著相关性(P = 0.001)。结论:卒中是尼日利亚住院患者的重要组成部分，其中缺血性卒中更为普遍。高死亡率强调了控制危险因素以预防中风的迫切需要。

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引用次数: 0

Noteworthy Disparities With Four CAQDAS Tools: Explorations in Organising Live Twitter Data 四种CAQDAS工具的显著差异:组织实时Twitter数据的探索

2区社会学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Social Science Computer Review

Pub Date : 2023-09-26 DOI: 10.1177/08944393231204163

Travis Noakes, Patricia Harpur, Corrie Uys

Qualitative data analysis software (QDAS) packages that support live data extraction are a relatively recent innovation. Little has been written concerning the research implications of differences in such QDAS packages’ functionalities, and how such disparities might contribute to contrasting analytical opportunities. Consequently, early-stage researchers may experience difficulties in choosing an apt QDAS for Twitter analysis. In response to both methodological gaps, this paper presents a software comparison across the four QDAS tools that support live Twitter data imports, namely, ATLAS.ti™, NVivo™, MAXQDA™ and QDA Miner™. The authors’ QDAS features checklist for these tools spotlights many differences in their functionalities. These disparities were tested through data imports and thematic coding that was derived from the same queries and codebook. The authors’ resultant QDAS experiences were compared during the first activity of a broad qualitative analysis process, ‘organising data’. Notwithstanding large difference in QDAS pricing, it was surprising how much the tools varied for aspects of qualitative research organisation. Notably, the quantum of data extracted for the same query differed, largely due to contrasts in the types and amount of data that the four QDAS could extract. Variations in how each supported visual organisation also shaped researchers’ opportunities for becoming familiar with Twitter users and their tweet content. Such disparities suggest that choosing a suitable QDAS for organising live Twitter data must dovetail with a researcher’s focus: ATLAS.ti accommodates scholars focused on wrangling unstructured data for personal meaning-making, while MAXQDA suits the mixed-methods researcher. QDA Miner’s easy-to-learn user interface suits a highly efficient implementation of methods, whilst NVivo supports relatively rapid analysis of tweet content. Such findings may help guide Twitter social science researchers and others in QDAS tool selection. Future research can explore disparities in other qualitative research phases, or contrast data extraction routes for a variety of microblogging services.

支持实时数据提取的定性数据分析软件(QDAS)软件包是一项相对较新的创新。很少有人写关于这些QDAS软件包功能差异的研究含义，以及这些差异如何有助于对比分析机会。因此，早期研究人员在选择适合Twitter分析的QDAS时可能会遇到困难。针对这两种方法上的差距，本文介绍了支持实时Twitter数据导入的四种QDAS工具(即ATLAS)的软件比较。ti™，NVivo™，MAXQDA™和QDA Miner™。作者的这些工具的QDAS特性清单突出了它们在功能上的许多差异。通过数据导入和源自相同查询和代码本的主题编码来测试这些差异。在广泛的定性分析过程的第一个活动“组织数据”中，比较了作者所得到的QDAS经验。尽管QDAS定价存在很大差异，但令人惊讶的是，这些工具在定性研究组织方面的差异有多大。值得注意的是，为同一查询提取的数据量不同，主要是由于四个QDAS可以提取的数据类型和数量的差异。每个人如何支持视觉组织的变化也塑造了研究人员熟悉Twitter用户和他们的Twitter内容的机会。这种差异表明，选择一个合适的QDAS来组织实时Twitter数据必须与研究人员的重点:ATLAS相吻合。它适用于专注于整理非结构化数据以进行个人意义生成的学者，而MAXQDA适用于混合方法研究人员。QDA Miner易于学习的用户界面适合高效的方法实施，而NVivo支持相对快速的tweet内容分析。这些发现可能有助于指导Twitter社会科学研究人员和其他QDAS工具选择。未来的研究可以探索其他定性研究阶段的差异，或者对比各种微博服务的数据提取路线。

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引用次数: 0

The Influence of Political Fit, Issue Fit, and Targeted Political Advertising Disclosures on Persuasion Knowledge, Party Evaluation, and Chilling Effects 政治契合度、议题契合度和针对性政治广告披露对说服知识、政党评价和寒蝉效应的影响

2区社会学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Social Science Computer Review

Pub Date : 2023-09-12 DOI: 10.1177/08944393231193731

Melanie Hirsch, Alice Binder, Jörg Matthes

The availability of online data has altered the role of social media. By offering targeted online advertising, that is, persuasive messages tailored to user groups, political parties profit from large data profiles to send fine-grained advertising appeals to susceptible voters. This between-subject experiment ( N = 421) investigates the influence of targeted political advertising disclosures (targeting vs. no-targeting disclosure), political fit (high vs. low), and issue fit (high vs. low) on recipients’ party evaluation and chilling effect intentions. The mediating role of targeting knowledge (TK) and perceived manipulative intent (PMI), two dimensions of persuasion knowledge, are investigated. The findings show that disclosing a targeting strategy and a high political fit activated individuals’ TK, that is, their recognition that their data had been used to show the ads, which then increased the evaluation of the political party and individuals’ intentions to engage in future chilling effect behaviors. High political fit decreased individuals’ reflections about the appropriateness of the targeted political ads (i.e., PMI), which then increased party evaluation. Issue fit did not affect individuals’ persuasion knowledge.

在线数据的可用性改变了社交媒体的角色。通过提供有针对性的在线广告，即针对用户群体量身定制的有说服力的信息，政党可以从大数据档案中获利，向易受影响的选民发送细粒度的广告吸引力。本被试间实验(N = 421)调查了有针对性的政治广告披露(有针对性与无针对性的披露)、政治契合度(高与低)和议题契合度(高与低)对接受者政党评价和寒战效应意图的影响。研究了说服知识的两个维度——目标知识(TK)和知觉操纵意图(PMI)的中介作用。研究结果表明，披露目标策略和高度的政治契合度激活了个人的TK，即他们对自己的数据被用于展示广告的认识，从而增加了对政党和个人参与未来寒蝉效应行为的意图的评估。高政治契合度降低了个人对目标政治广告恰当性的反思(即PMI)，进而提高了政党评价。议题契合度不影响个体的说服知识。

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引用次数: 0

Cheap, Quick, and Rigorous: Artificial Intelligence and the Systematic Literature Review 廉价、快速、严谨:人工智能与系统文献综述

IF 4.1 2区社会学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Social Science Computer Review

Pub Date : 2023-08-26 DOI: 10.1177/08944393231196281

Cameron F. Atkinson

The systematic literature review (SLR) is the gold standard in providing research a firm evidence foundation to support decision-making. Researchers seeking to increase the rigour, transparency, and replicability of their SLRs are provided a range of guidelines towards these ends. Artificial Intelligence (AI) and Machine Learning Techniques (MLTs) developed with computer programming languages can provide methods to increase the speed, rigour, transparency, and repeatability of SLRs. Aimed towards researchers with coding experience, and who want to utilise AI and MLTs to synthesise and abstract data obtained through a SLR, this article sets out how computer languages can be used to facilitate unsupervised machine learning for synthesising and abstracting data sets extracted during a SLR. Utilising an already known qualitative method, Deductive Qualitative Analysis, this article illustrates the supportive role that AI and MLTs can play in the coding and categorisation of extracted SLR data, and in synthesising SLR data. Using a data set extracted during a SLR as a proof of concept, this article will include the coding used to create a well-established MLT, Topic Modelling using Latent Dirichlet allocation. This technique provides a working example of how researchers can use AI and MLTs to automate the data synthesis and abstraction stage of their SLR, and aide in increasing the speed, frugality, and rigour of research projects.

系统文献综述（SLR）是为研究提供坚实证据基础以支持决策的黄金标准。寻求提高SLR的严格性、透明度和可复制性的研究人员为此提供了一系列指导方针。使用计算机编程语言开发的人工智能（AI）和机器学习技术（MLT）可以提供提高单反速度、严格性、透明度和可重复性的方法。本文针对有编码经验的研究人员，他们希望利用人工智能和MLT来合成和抽象通过单反获得的数据，阐述了如何使用计算机语言来促进无监督机器学习，以合成和抽象单反过程中提取的数据集。本文利用一种已知的定性方法——演绎定性分析，说明了人工智能和MLT在提取的单反数据的编码和分类以及合成单反数据中可以发挥的支持作用。使用SLR期间提取的数据集作为概念证明，本文将包括用于创建完善的MLT的编码，即使用潜在狄利克雷分配的主题建模。这项技术提供了一个工作示例，说明研究人员如何使用人工智能和MLT来自动化SLR的数据合成和抽象阶段，并有助于提高研究项目的速度、节约和严格性。

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引用次数: 1

Novelty in News Search: A Longitudinal Study of the 2020 US Elections 新闻搜索中的新颖性:对2020年美国大选的纵向研究

2区社会学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Social Science Computer Review

Pub Date : 2023-08-14 DOI: 10.1177/08944393231195471

Roberto Ulloa, Mykola Makhortykh, Aleksandra Urman, Juhi Kulshrestha

The 2020 US elections news coverage was extensive, with new pieces of information generated rapidly. This evolving scenario presented an opportunity to study the performance of search engines in a context in which they had to quickly process information as it was published. We analyze novelty, a measurement of new items that emerge in the top news search results, to compare the coverage and visibility of different topics. Using virtual agents that simulate human web browsing behavior to collect search engine result pages, we conduct a longitudinal study of news results of five search engines collected in short bursts (every 21 minutes) from two regions (Oregon, US and Frankfurt, Germany), starting on election day and lasting until one day after the announcement of Biden as the winner. We find more new items emerging for election related queries (“joe biden,” “donald trump,” and “us elections”) compared to topical (e.g., “coronavirus”) or stable (e.g., “holocaust”) queries. We demonstrate that our method captures sudden changes in highly covered news topics as well as multiple differences across search engines and regions over time. We highlight novelty imbalances between candidate queries which affect their visibility during electoral periods, and conclude that, when it comes to news, search engines are responsible for such imbalances, either due to their algorithms or the set of news sources that they rely on.

2020年美国大选的新闻报道非常广泛，新信息层出不穷。这个不断发展的场景提供了一个研究搜索引擎在发布信息时必须快速处理的环境中的性能的机会。我们分析新颖性，即在新闻搜索结果中出现的新项目的衡量标准，以比较不同主题的覆盖率和可见性。使用模拟人类网络浏览行为的虚拟代理来收集搜索引擎结果页面，我们对从两个地区(美国俄勒冈州和德国法兰克福)以短时间(每21分钟)收集的五个搜索引擎的新闻结果进行了纵向研究，从选举日开始，一直持续到宣布拜登获胜后的一天。我们发现，与选举相关的查询(“乔·拜登”、“唐纳德·特朗普”和“美国选举”)相比，热门查询(如“冠状病毒”)或稳定查询(如“大屠杀”)出现了更多的新条目。我们证明，我们的方法可以捕捉到新闻主题的突然变化，以及搜索引擎和地区之间随时间的多种差异。我们强调了候选人查询之间的新颖性不平衡，这影响了他们在选举期间的可见性，并得出结论，当涉及到新闻时，搜索引擎要对这种不平衡负责，要么是由于他们的算法，要么是他们所依赖的新闻来源。

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引用次数: 0

The Impact of Economic Degradation on the Uí Bhriain Civil War (1276–1318): An Agent-Based Modeling Approach 经济衰退对乌比里亚内战的影响（1276-1318）：一种基于Agent的建模方法

IF 4.1 2区社会学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Social Science Computer Review

Pub Date : 2023-08-12 DOI: 10.1177/08944393231194983

Vinicius Marino Carvalho

Between 1276 and 1318, English magnates unsuccessfully attempted to establish a lordship in the Irish kingdom of Thomond, southwestern Ireland, by exploiting a dynastic feud dividing the then-ruling lineage, the Uí Bhriain. The conflict coincided with a series of extreme events that beset western Europe in the late 13th and early 14th centuries, such as the beginning of the Little Ice Age and the Great European Famine of 1315–1322. The goal of this work was to evaluate to the extent to which economic degradation at the turn of the 14th century affected the outcome of the war. The hypothesis that such degradation affected the war’s outcome was tested using agent-based modeling, which involved the virtual reconstruction of Late Medieval Thomond to study past conditions by proxy. This article describes the historical research carried out to elaborate the conceptual model, the implementation of the model as a computer simulation, and the experiments carried out to virtually explore the Uí Bhriain Civil War. A quantitative analysis of the experimental results revealed some correlation between late 13th century economic degradation and the fortunes of belligerent factions in the wars of 1276–1318, although the effect was not sufficiently strong to have been a crucial factor in the outcome of the conflict.

1276年至1318年间，英国巨头们试图利用当时统治家族UíBhriain的王朝不和，在爱尔兰西南部的爱尔兰托蒙德王国建立贵族地位，但没有成功。这场冲突恰逢13世纪末和14世纪初困扰西欧的一系列极端事件，如小冰河时代的开始和1315-1322年的欧洲大饥荒。这项工作的目标是评估14世纪之交的经济衰退对战争结果的影响程度。这种退化影响战争结果的假设使用基于代理的建模进行了测试，该建模涉及中世纪晚期托蒙德的虚拟重建，以通过代理研究过去的情况。本文描述了为阐述概念模型而进行的历史研究，将模型作为计算机模拟的实现，以及为虚拟探索乌比里亚内战而进行的实验。对实验结果的定量分析揭示了13世纪末的经济衰退与1276-1318年战争中交战派系的命运之间的一些相关性，尽管这种影响还不足以成为冲突结果的关键因素。

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引用次数: 0

Cyberbullying and Traditional Bullying Victimization, Depressive Symptoms, and Suicidal Ideation Among Chinese Early Adolescents: Cognitive Reappraisal and Emotion Invalidation as Moderators 中国早期青少年的网络欺凌、传统欺凌受害、抑郁症状和自杀意念:认知重评和情绪无效是调节因素

IF 4.1 2区社会学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Social Science Computer Review

Pub Date : 2023-08-02 DOI: 10.1177/08944393231192237

Jianhua Zhou, Haiyan Zhao, Yan Zou

This study examined how depressive symptoms play mediating roles between cyberbullying and traditional bullying victimization and suicidal ideation and the moderating roles of cognitive reappraisal and emotion invalidation. A total of 1,823 Chinese adolescents (Mean age = 11.20, SD = 1.21, 47.8% girls) participated this study. Results showed that cyberbullying victimization was more strongly related to suicidal ideation than traditional bullying victimization. Depressive symptoms played mediating roles between cyberbullying and traditional bullying victimization and suicidal ideation. Cognitive reappraisal mitigated the effects of cyberbullying and traditional bullying victimization on depressive symptoms, and perceived emotion invalidation strengthened the effect of depressive symptoms on suicidal ideation. Results further showed that the mediating effect of depressive symptoms was more prominent when there were low levels of cognitive reappraisal and more perceived emotion invalidation. Promoting youths’ cognitive reappraisal and providing validating responses to their depressive symptoms could mitigate the destructive effects of bullying victimization on suicidal ideation.

本研究探讨了抑郁症状在网络欺凌、传统欺凌受害和自杀意念之间的中介作用，以及认知重评和情绪失效的调节作用。共有1823名中国青少年参与本研究，平均年龄为11.20岁，SD = 1.21，其中47.8%为女生。结果表明，网络欺凌受害与自杀意念的关系比传统欺凌受害更强。抑郁症状在网络欺凌、传统欺凌受害和自杀意念之间起中介作用。认知重评减轻了网络欺凌和传统欺凌受害对抑郁症状的影响，感知情绪失能强化了抑郁症状对自杀意念的影响。结果进一步表明，认知重评水平低、情绪失能程度高时，抑郁症状的中介作用更为突出。促进青少年对抑郁症状的认知重新评估和提供有效的回应可以减轻欺凌受害对自杀意念的破坏性影响。

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引用次数: 0

Participatory Inequality Across Countries: Contacting Public Officials Online and Offline. 各国的参与性不平等:与政府官员的线上和线下联系。

IF 4.1 2区社会学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Social Science Computer Review

Pub Date : 2023-08-01 DOI: 10.1177/08944393211071067

Shelley Boulianne

The Internet offers low-cost ways to participate in political life, which reduces the motivation required to participate and thus potentially reduces inequalities in participation. I examine online and offline contacting of elected officials using original survey data from Canada, France, the United Kingdom, and the United States collected in 2019 and 2021. Education is a consistent positive predictor of contacting in all countries as well as both modes of contact (online and offline). Income differences are small. Younger people are more likely to contact officials, online and offline, compared to older people. Females are less likely to contact officials, online and offline, compared to males. While political interest, efficacy, online information consumption, and online group ties are believed to lead to more equity in online communication, I do not see strong differences in these variables for online and offline contacting. I conclude by discussing the implications of exclusively online contacting of officials when this form of contact is devalued by elected officials, as well as the implications of participatory inequalities with respect to influencing public policy and access to government services.

互联网提供了参与政治生活的低成本方式，这降低了参与所需的动机，从而可能减少参与方面的不平等。我使用2019年和2021年从加拿大、法国、英国和美国收集的原始调查数据，研究了民选官员的在线和离线联系。教育在所有国家以及两种接触模式(在线和离线)中都是一个一致的积极预测因素。收入差距很小。与老年人相比，年轻人更有可能在网上和线下与官员联系。与男性相比，女性在网上和线下与官员接触的可能性更小。虽然政治兴趣、有效性、在线信息消费和在线群体关系被认为会导致在线交流中更多的公平，但我没有看到这些变量在在线和离线联系中有很大的差异。最后，我讨论了当这种形式的接触被民选官员贬低时，官员完全在线接触的影响，以及参与性不平等在影响公共政策和获得政府服务方面的影响。

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引用次数: 4