Social Science Computer Review最新文献

Testing Motivation-Based vs. Social Exchange Communication Strategies in Email Survey Recruitment

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2024-12-18 DOI: 10.1177/08944393241308509

Jason Kosakow, Pierce Greenberg

{"title":"Testing Motivation-Based vs. Social Exchange Communication Strategies in Email Survey Recruitment","authors":"Jason Kosakow, Pierce Greenberg","doi":"10.1177/08944393241308509","DOIUrl":"https://doi.org/10.1177/08944393241308509","url":null,"abstract":"Despite well-documented challenges, researchers across the social sciences continue to rely on email to recruit research participants. However, few studies examine how different communication strategies impact email open and conversion rates, especially among surveys of establishments. Our paper aims to fill that gap by examining whether motivation-based appeals—which we develop from respondents’ reasons for participating—outperform a communication approach based on social exchange theory. Our study identified the top three motivations why current panel members participate in the Federal Reserve Bank of Richmond Business Survey: (1) access to data and other benefits, (2) the ability to influence economic policy, and (3) to help make their communities better. Then, we crafted email subject lines and messages to match those three motivations and a version based on tenets of social exchange theory. Our results find that the social exchange version outperforms the motivation-based appeals in both email open and conversion rates—with a stronger influence on conversion rates. We discuss the implications of these results for how social science researchers communicate with potential research participants by email.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"22 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142841942","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

Asking for Traces: A Vignette Study on Acceptability Norms and Personal Willingness to Donate Digital Trace Data

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2024-12-09 DOI: 10.1177/08944393241305776

Henning Silber, Johannes Breuer, Barbara Felderer, Frederic Gerdon, Patrick Stammann, Jessica Daikeler, Florian Keusch, Bernd Weiß

{"title":"Asking for Traces: A Vignette Study on Acceptability Norms and Personal Willingness to Donate Digital Trace Data","authors":"Henning Silber, Johannes Breuer, Barbara Felderer, Frederic Gerdon, Patrick Stammann, Jessica Daikeler, Florian Keusch, Bernd Weiß","doi":"10.1177/08944393241305776","DOIUrl":"https://doi.org/10.1177/08944393241305776","url":null,"abstract":"Digital trace data are increasingly used in the social sciences. Given the risks associated with data access via application programming interfaces (APIs) as well as ethical discussions around the use of such data, data donations have been proposed as a methodologically reliable and ethically sound way of collecting digital trace data. While data donations have many advantages, study participants may be reluctant to share their data, for example, due to privacy concerns. To assess which factors in a data donation request are relevant for participants’ acceptance and decisions, we conducted a vignette experiment investigating the general acceptability and personal willingness to donate various data types (i.e., data from GPS, web browsing, LinkedIn/Xing, Facebook, and TikTok) for research purposes. The preregistered study was implemented in the probability-based German Internet Panel (GIP) and gathered responses from n = 3821 participants. Results show that people rate the general acceptability of data donation requests higher than their own willingness to donate data. Regarding the different data types, respondents indicated that they would be more willing to donate their LinkedIn/Xing, TikTok, and GPS data compared to web browsing and Facebook data. In contrast, information about whether the donated data would be shared with other researchers and data security did not affect the responses to the respective donation scenarios. Based on these results, we discuss implications for studies employing data donations.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"83 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142796796","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

People, Platforms, and Places: The Conditional Effects of Psychological Distances on Livestream Viewership

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2024-12-02 DOI: 10.1177/08944393241305780

Zhang Hao Goh, Minzheng Hou, Edson C. Tandoc

引用次数: 0

Has ChatGPT Disrupted the Education Sector in the U.S.? ChatGPT 是否颠覆了美国的教育领域？

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2024-11-22 DOI: 10.1177/08944393241301330

Erik Haugom, Štefan Lyócsa, Martina Halousková

{"title":"Has ChatGPT Disrupted the Education Sector in the U.S.?","authors":"Erik Haugom, Štefan Lyócsa, Martina Halousková","doi":"10.1177/08944393241301330","DOIUrl":"https://doi.org/10.1177/08944393241301330","url":null,"abstract":"The introduction of ChatGPT and other tools based on artificial intelligence (AI) has the potential to revolutionize the field of education. We study how the public release of ChatGPT and the increased attention on this new large language model from OpenAI are associated with the expected returns of publicly traded firms that operate in the education sector. We also perform separate subgroup analyses for the traditional education sector and the so-called education technology sector. Using linear and threshold CAPM-GARCH models, we find that after the public release of ChatGPT, both the education sector as a whole and the education technology sector have underperformed benchmarks. Our results show that increased attention leads to lower next-day returns in the education sector as a whole and the education technology sector in particular. Additionally, during periods of higher attention, expected returns tend to decline in these two sectors. We also show that the introduction of ChatGPT or the increased interest in this AI tool in the population does not affect the traditional education sector. The introduction of ChatGPT thus has a heterogeneous effect across the various education sectors we examine, with the education technology sector receiving most of the disruption.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"24 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142690779","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

The Moderating Role of Self-Esteem in the Relationship Between Social Media Use and Life Satisfaction Among Older Adults 自尊在社交媒体使用与老年人生活满意度关系中的调节作用

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2024-11-15 DOI: 10.1177/08944393241301045

Yesolran Kim

引用次数: 0

Feminist Identity and Online Activism in Four Countries From 2019 to 2023 2019 年至 2023 年四个国家的女权主义者身份和网络活动

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2024-11-15 DOI: 10.1177/08944393241301050

Shelley Boulianne, Katharina Heger, Nicole Houle, Delphine Brown

{"title":"Feminist Identity and Online Activism in Four Countries From 2019 to 2023","authors":"Shelley Boulianne, Katharina Heger, Nicole Houle, Delphine Brown","doi":"10.1177/08944393241301050","DOIUrl":"https://doi.org/10.1177/08944393241301050","url":null,"abstract":"The COVID-19 pandemic heightened burdens on caregivers, but also the visibility of caregiving inequalities. These grievances may activate a feminist identity which in turn leads to greater civic and political participation. During a pandemic, online forms of participation are particularly attractive as they require less effort than offline forms of participation and pose less health risks compared to collective forms of offline activism. Using survey data from four countries (Canada, France, the United States, and the United Kingdom) collected in 2019 (prior to the pandemic), 2021 (during the pandemic), and 2023 (post-pandemic), we examine the relationship between self-identifying as a feminist and signing online petitions ( n = 18,362). Our multivariate analyses show that having a feminist identity is positively related to signing online petitions. We consider the differential effects of this identity on participation for men, women, non-binary people; caregivers versus non-caregivers; and respondents in different countries with varying levels of restrictions due to the pandemic. A feminist identity is more important for mobilizing caregivers than non-caregivers, whether or not the caregiver is a man or a woman. While grievance theory suggests differential effects by country and time period, we find a consistent role of feminist identity in predicting the signing of online petitions across time and across countries. These findings offer insights into how different groups in varying contexts are mobilized to participate.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"16 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142642987","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

Improving the Quality of Individual-Level Web Tracking: Challenges of Existing Approaches and Introduction of a New Content and Long-Tail Sensitive Academic Solution 提高个人层面网络跟踪的质量：现有方法面临的挑战与新内容和长尾敏感学术解决方案的介绍

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2024-10-16 DOI: 10.1177/08944393241287793

Silke Adam, Mykola Makhortykh, Michaela Maier, Viktor Aigenseer, Aleksandra Urman, Teresa Gil Lopez, Clara Christner, Ernesto de León, Roberto Ulloa

{"title":"Improving the Quality of Individual-Level Web Tracking: Challenges of Existing Approaches and Introduction of a New Content and Long-Tail Sensitive Academic Solution","authors":"Silke Adam, Mykola Makhortykh, Michaela Maier, Viktor Aigenseer, Aleksandra Urman, Teresa Gil Lopez, Clara Christner, Ernesto de León, Roberto Ulloa","doi":"10.1177/08944393241287793","DOIUrl":"https://doi.org/10.1177/08944393241287793","url":null,"abstract":"This article evaluates the quality of data collection in individual-level desktop web tracking used in the social sciences and shows that the existing approaches face sampling issues, validity issues due to the lack of content-level data and their disregard for the variety of devices and long-tail consumption patterns as well as transparency and privacy issues. To overcome some of these problems, the article introduces a new academic web tracking solution, WebTrack, an open-source tracking tool maintained by a major European research institution, GESIS. The design logic, the interfaces, and the backend requirements for WebTrack are discussed, followed by a detailed examination of the strengths and weaknesses of the tool. Finally, using data from 1,185 participants, the article empirically illustrates how an improvement in data collection through WebTrack leads to innovative shifts in the use of tracking data. As WebTrack allows for collecting the content people are exposed to beyond the classical news platforms, it can greatly improve the detection of politics-related information consumption in tracking data through automated content analysis compared to traditional approaches that rely on the source-level analysis.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"1 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142444489","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

Can AI Lie? Chabot Technologies, the Subject, and the Importance of Lying 人工智能会说谎吗？查博特技术、研究对象和说谎的重要性

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2024-10-16 DOI: 10.1177/08944393241282602

Jack Black

{"title":"Can AI Lie? Chabot Technologies, the Subject, and the Importance of Lying","authors":"Jack Black","doi":"10.1177/08944393241282602","DOIUrl":"https://doi.org/10.1177/08944393241282602","url":null,"abstract":"This article poses a simple question: can AI lie? In response to this question, the article examines, as its point of inquiry, popular AI chatbots, such as, ChatGPT. In doing so, an examination of the psychoanalytic, philosophical, and technological significance of AI and its complexities are located in relation to the dynamics of truth, falsity, and deception. That is, by critically considering the chatbot’s ability to engage in natural language conversations and provide contextually relevant responses, it is argued that what separates the AI chatbot from anthropocentric debates, which allude to some form of conscious recognition on behalf of AI, is the importance of the lie – an importance which a psychoanalytic approach can reveal. Indeed, while AI technologies can undoubtedly blur the line between lies and truth-speaking, in the case of the AI chatbot, it is detailed how such technology remains unable to lie authentically or, in other words, is unable to lie like a human. For psychoanalysis, the capacity to lie bears witness to the unconscious and, thus, plays an important role in determining the subject. It is for this reason that rather than uncritically accepting the chatbot’s authority – an authority that is easily reflected in its honest responses and frank admissions – a psychoanalytic (Lacanian) perspective can highlight the significance of the unconscious as a distorting factor in determining the subject. To help elucidate this argument, specific attention is given to introducing and applying Lacan’s subject of enunciation and subject of the enunciated. This is used to assert that what continues (for now) to set us apart from AI technology is not necessarily our ‘better knowledge’ but our capability to consciously engage in acts of falsehood that function to reveal the social nuances and significances of the lie.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"231 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142444488","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

Using Google Trends Data to Study High-Frequency Search Terms: Evidence for a Reliability-Frequency Continuum 利用谷歌趋势数据研究高频搜索词：可靠性-频率连续性的证据

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2024-10-12 DOI: 10.1177/08944393241279421

Tobias Gummer, Anne-Sophie Oehrlein

{"title":"Using Google Trends Data to Study High-Frequency Search Terms: Evidence for a Reliability-Frequency Continuum","authors":"Tobias Gummer, Anne-Sophie Oehrlein","doi":"10.1177/08944393241279421","DOIUrl":"https://doi.org/10.1177/08944393241279421","url":null,"abstract":"Google Trends (GT) data are increasingly used in the social sciences and adjacent fields. However, previous research on the quality of GT data has raised concerns regarding their reliability. In the present study, we investigated whether reliability differs between low- and high-frequency search terms. In other words, we explored the existence of a reliability-frequency continuum in GT data. Our study adds to previous research by investigating a more comprehensive set of search terms and different aspects of reliability (e.g., differences in relative search volume distributions, correctly identified maxima). For this purpose, we collected samples of GT data for ten high- and two low-frequency search terms. We obtained one real-time sample and 62 non–realtime samples per search term (30 non–realtime samples for low-frequency search terms). Data collection was restricted to search data for Germany. Our data support the existence of a reliability-frequency continuum—low-frequency search terms are subject to greater reliability issues compared to high-frequency search terms. Based on our findings, we have derived practical recommendations for the use of GT data and have outlined future research opportunities.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"8 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142430476","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

Large Language Models Outperform Expert Coders and Supervised Classifiers at Annotating Political Social Media Messages 大语言模型在注释政治社交媒体信息方面优于专家编码员和监督分类器

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2024-09-23 DOI: 10.1177/08944393241286471

Petter Törnberg

{"title":"Large Language Models Outperform Expert Coders and Supervised Classifiers at Annotating Political Social Media Messages","authors":"Petter Törnberg","doi":"10.1177/08944393241286471","DOIUrl":"https://doi.org/10.1177/08944393241286471","url":null,"abstract":"Instruction-tuned Large Language Models (LLMs) have recently emerged as a powerful new tool for text analysis. As these models are capable of zero-shot annotation based on instructions written in natural language, they obviate the need of large sets of training data—and thus bring potential paradigm-shifting implications for using text as data. While the models show substantial promise, their relative performance compared to human coders and supervised models remains poorly understood and subject to significant academic debate. This paper assesses the strengths and weaknesses of popular fine-tuned AI models compared to both conventional supervised classifiers and manual annotation by experts and crowd workers. The task used is to identify the political affiliation of politicians based on a single X/Twitter message, focusing on data from 11 different countries. The paper finds that GPT-4 achieves higher accuracy than both supervised models and human coders across all languages and country contexts. In the US context, it achieves an accuracy of 0.934 and an inter-coder reliability of 0.982. Examining the cases where the models fail, the paper finds that the LLM—unlike the supervised models—correctly annotates messages that require interpretation of implicit or unspoken references, or reasoning on the basis of contextual knowledge—capacities that have traditionally been understood to be distinctly human. The paper thus contributes to our understanding of the revolutionary implications of LLMs for text analysis within the social sciences.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"27 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142313736","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