Research Methods for Digital Work and Organization最新文献

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Digital Diaries as a Research Method for Capturing Practices in Situ 数字日记作为一种实地捕捉实践的研究方法
Research Methods for Digital Work and Organization Pub Date : 2021-10-21 DOI: 10.1093/oso/9780198860679.003.0006
M. H. Jarrahi, Cami Goray, S. Zirker, Yinglong Zhang
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引用次数: 4
Structuring the Haystack 构建干草堆
Research Methods for Digital Work and Organization Pub Date : 2021-10-21 DOI: 10.1093/oso/9780198860679.003.0013
E. Bucher, P. Schou, Matthias Waldkirch, Eduard Grünwald, David Antons
{"title":"Structuring the Haystack","authors":"E. Bucher, P. Schou, Matthias Waldkirch, Eduard Grünwald, David Antons","doi":"10.1093/oso/9780198860679.003.0013","DOIUrl":"https://doi.org/10.1093/oso/9780198860679.003.0013","url":null,"abstract":"Large-scale online communities, such as Reddit or Quora, have emerged as promising research contexts, offering insight into an unprecedented range of real-time user discourses. However, researchers striving to access, collect, and meaningfully process such conversation data face a trade-off between capturing breadth (structures, relationships) and depth (content, meaning) of community interactions. Building on a mixed-methodology design, our contribution offers an avenue to harness and combine advantages of both approaches, first by clustering the data based on a theoretically derived dictionary (discovering structure) and second by qualitatively coding and interpreting the resulting clusters (discovering meaning). We illustrate this methodological approach with data collected from a community of online workers on Reddit where we focused on how human resource management (HRM) practices transform in the gig economy and how digital platforms use a hybrid HRM system that combines elements of high-performance and control-oriented HRM philosophies.","PeriodicalId":156019,"journal":{"name":"Research Methods for Digital Work and Organization","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129363776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Research Methods to Study and Empower Crowd Workers 研究和授权群体工作者的研究方法
Research Methods for Digital Work and Organization Pub Date : 2021-10-21 DOI: 10.1093/oso/9780198860679.003.0009
Saiph Savage, C. Toxtli, Eber Betanzos-Torres
{"title":"Research Methods to Study and Empower Crowd Workers","authors":"Saiph Savage, C. Toxtli, Eber Betanzos-Torres","doi":"10.1093/oso/9780198860679.003.0009","DOIUrl":"https://doi.org/10.1093/oso/9780198860679.003.0009","url":null,"abstract":"The artificial intelligence (AI) industry has created new jobs that are essential to the real world deployment of intelligent systems. Part of the job focuses on labelling data for machine learning models or having workers complete tasks that AI alone cannot do. These workers are usually known as ‘crowd workers’—they are part of a large distributed crowd that is jointly (but separately) working on the tasks although they are often invisible to end-users, leading to workers often being paid below minimum wage and having limited career growth. In this chapter, we draw upon the field of human–computer interaction to provide research methods for studying and empowering crowd workers. We present our Computational Worker Leagues which enable workers to work towards their desired professional goals and also supply quantitative information about crowdsourcing markets. This chapter demonstrates the benefits of this approach and highlights important factors to consider when researching the experiences of crowd workers.","PeriodicalId":156019,"journal":{"name":"Research Methods for Digital Work and Organization","volume":"250 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133734684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Me, Myself, and iPhone 我,我自己和iPhone
Research Methods for Digital Work and Organization Pub Date : 2021-10-21 DOI: 10.1093/oso/9780198860679.003.0004
Adam Badger
{"title":"Me, Myself, and iPhone","authors":"Adam Badger","doi":"10.1093/oso/9780198860679.003.0004","DOIUrl":"https://doi.org/10.1093/oso/9780198860679.003.0004","url":null,"abstract":"This chapter explores methodological approaches to the study of gig economy work through the deployment of the researcher’s smartphone. Set within the context of a covert ethnography of a delivery platform in London, the phone became a site to both experience work and record empirical findings in the workplace. Specifically, this chapter considers the sociomaterial construction and performance of the smartphone at work to highlight how its capacities and affordances shaped the empirical output. Critical reflections on the limits of the smartphone work alongside reflexive considerations of the researching self to position the researcher and phone as active agents in the research process; in which methodological decisions bear impacts on the nature of the empirical material produced. Of particular significance is the deployment of various apps, tailored to the needs of the field site and research to create diverse, multi-modal datasets, in addition to their synthesis into a coherent and curated ethnographic field diary for subsequent analysis.","PeriodicalId":156019,"journal":{"name":"Research Methods for Digital Work and Organization","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134608482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
After Vanity Metrics 虚荣参数之后
Research Methods for Digital Work and Organization Pub Date : 2021-10-21 DOI: 10.1093/oso/9780198860679.003.0014
R. Rogers
{"title":"After Vanity Metrics","authors":"R. Rogers","doi":"10.1093/oso/9780198860679.003.0014","DOIUrl":"https://doi.org/10.1093/oso/9780198860679.003.0014","url":null,"abstract":"‘Vanity metrics,’ as they are critically termed, measure the performative work an individual carries out on social media. Posting on social media and subsequently displaying and maintaining like, view, and follow counts have been critiqued as both distracting modes of engagement as well as performance in a ‘success theater’. The notion of vanity metrics additionally implies how one may consider reworking the metrics. In an undertaking he calls ‘critical analytics’, the author proposes an alternative metrics project akin to altmetrics in science but utilized instead to measure actor activity around social issues and causes in social media. Critical analytics are means to analyse dominant voice, concern, commitment, positioning, and alignment of actors using social media to work on social issues and causes, seeking to contribute a conceptual and applied research agenda to orient the study of social media use and activity metrics.","PeriodicalId":156019,"journal":{"name":"Research Methods for Digital Work and Organization","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126613868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Thick Big Data 厚大数据
Research Methods for Digital Work and Organization Pub Date : 2020-03-25 DOI: 10.1093/oso/9780198839705.001.0001
D. Jemielniak
{"title":"Thick Big Data","authors":"D. Jemielniak","doi":"10.1093/oso/9780198839705.001.0001","DOIUrl":"https://doi.org/10.1093/oso/9780198839705.001.0001","url":null,"abstract":"The social sciences are becoming datafied. The questions that have been considered the domain of sociologists, now are answered by data scientists, operating on large datasets, and breaking with the methodological tradition for better or worse. The traditional social sciences, such as sociology or anthropology, are thus under the double threat of becoming marginalized or even irrelevant; both because of the new methods of research, which require more computational skills, and because of the increasing competition from the corporate world, which gains an additional advantage based on data access. However, sociologists and anthropologists still have some important assets, too. Unlike data scientists, they have a long history of doing qualitative research. The more quantified datasets we have, the more difficult it is to interpret them without adding layers of qualitative interpretation. Big Data needs Thick Data. This book presents the available arsenal of new tools for studying the society quantitatively, but also show the new methods of analysis from the qualitative side and encourages their combination. In shows that Big Data can and should be supplemented and interpreted through thick data, as well as cultural analysis, in a novel approach of Thick Big Data.The book is critically important for students and researchers in the social sciences to understand the possibilities of digital analysis, both in the quantitative and qualitative area, and successfully build mixed-methods approaches.","PeriodicalId":156019,"journal":{"name":"Research Methods for Digital Work and Organization","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129277830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 22
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