Saving social media data: Understanding data management practices among social media researchers and their implications for archives

Hemphill, Libby; Hedstrom, Margaret; Leonard, Susan Hautaniemi

doi:10.1002/asi.24368

Cited by 19 publications

(24 citation statements)

References 73 publications

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“…Social media users share sensitive and highly personal information, but it is unclear whether they are aware that their data may be used for scientific research (Hemphill et al , 2021). Such users might feel very uncomfortable once they learn that their data were collected and used.…”

Section: Literature Reviewmentioning

confidence: 99%

Determining factors of participants' attitudes toward the ethics of social media data research

Cui

Chen

2021

OIR

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PurposeThe purpose of this study was to investigate the participants' attitudes toward the ethical issues caused by collecting social media data (SMD) for research, as well as the effects of familiarity, trust and altruism on the participants' attitudes toward the ethics of SMD research. It is hoped that through this study, scholars will be reminded to respect participants and engage in ethical reflection when using SMD in research.Design/methodology/approachThis study adopted social media users as its research subjects and used Sina Microblog, the world's largest Chinese social media platform, as the example. Based on the 320 valid responses collected from a survey, structural equation modeling was employed to examine the research model.FindingsThe results indicated that altruism, familiarity and trust have significant influences on participants' attitudes toward the ethics of SMD research, and familiarity also influences attitudes through the mediating role of trust and altruism.Originality/valueThis study explored the mechanism underlying the relationship between the determining factors and participants' attitudes toward the ethics of SMD research, and the results demonstrated that the informed consent mechanism is an effective way to communicate with participants and that the guiding responsibility of the platform should be improved to standardize SMD research.

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Section: Literature Reviewmentioning

confidence: 99%

Determining factors of participants' attitudes toward the ethics of social media data research

Cui

Chen

2021

OIR

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“…Machine learning, computer vision, and social media studies often use "found" data [Hemphill et al 2021;Jo and Gebru 2020;Paullada et al 2021] and render curatorial decisions such as "what data should be available, " "in which format(s) should data be provided, " or "how should this data be sampled" invisible. For instance, datasets scraped from the web (such as Flickr photos [Scheuerman et al 2021;Zhang et al 2015] or Wikipedia talk pages [Wulczyn et al 2016[Wulczyn et al , 2017) suffer from biases in representation [Jo and Gebru 2020].…”

Section: What Renders Data Curation Invisible?mentioning

confidence: 99%

The craft and coordination of data curation: complicating "workflow" views of data science

Thomer¹,

Akmon²,

Jeremy³

et al. 2022

Preprint

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Data curation is the process of making a dataset fit-for-use and archiveable. It is critical to data-intensive science because it makes complex data pipelines possible, makes studies reproducible, and makes data (re)usable. Yet the complexities of the hands-on, technical and intellectual work of data curation is frequently overlooked or downplayed. Obscuring the work of data curation not only renders the labor and contributions of the data curators invisible; it also makes it harder to tease out the impact curators' work has on the later usability, reliability, and reproducibility of data. To better understand the specific work of data curation -and thereby, explore ways of showing curators' impact -we conducted a close examination of data curation at a large social science data repository, the Inter-university Consortium of Political and Social Research (ICPSR). We asked, What does curatorial work entail at ICPSR, and what work is more or less visible to different stakeholders and in different contexts? And, how is that curatorial work coordinated across the organization? We triangulate accounts of data curation from interviews and records of curation in Jira tickets to develop a rich and detailed account of curatorial work. We find that curators describe a number of craft practices needed to perform their work, which defies the rote sequence of events implied by many lifecycle or workflow models. Further, we show how best practices and craft practices are deeply intertwined. CCS Concepts: • Human-centered computing → Collaborative and social computing systems and tools; • Applied computing → Document preparation; • Information systems → Digital libraries and archives.

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“…It is possible to identify many reasons that triggered such debates on existing infrastructures. One factor lies in the vast amounts of data and metadata produced in the course of today's dataintensive science (Corujo;Silva;Revez, 2016;Hemphill;Leonard;Hedstrom, 2020). This boom in value is paired with an increase in the variety of formats and representations, which, by itself, complicates the mission of interoperability, understood as "[…] the ability of data or tools from noncooperating resources to integrate or work together with minimal effort" (Wilkinson et al, 2016, p. 2).…”

Section: Structure Of a Fair Accessormentioning

confidence: 99%

The FAIR Accessor and the authenticity of digital archival information

2022

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The constant increase in digital information’s volume, variety, and complexity poses many problems that make it difficult to preserve archival information while ensuring that it remains authentic, reliable, accessible, trustworthy, intelligible, and reusable for as long as possible. This study explores the concepts of a possible implementation of a FAIR Accessor, a technology developed to provide Findable, Accessible, Interoperable, and Reusable research data, as an infrastructure that can support and aid archival information description and ensure its authenticity. A qualitative literature review on a selection of representative works in the fields of Information Science, Diplomatics, and the FAIR principles is followed by a discussion on how the key concepts of each field overlay and thus may complement each other mutually. It is concluded that the infrastructure of the FAIR Accessor can prove useful in enriching archival description and, ultimately, in assisting to ascertaining the authenticity of records.

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Saving social media data: Understanding data management practices among social media researchers and their implications for archives

Cited by 19 publications

References 73 publications

Determining factors of participants' attitudes toward the ethics of social media data research

Determining factors of participants' attitudes toward the ethics of social media data research

The craft and coordination of data curation: complicating "workflow" views of data science

The FAIR Accessor and the authenticity of digital archival information

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