The Heart Work of Wikipedia

Menking, Amanda; Erickson, Ingrid

doi:10.1145/2702123.2702514

Cited by 83 publications

(43 citation statements)

References 19 publications

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“…Overall this suggests that the populations we focused on (although with only a small, qualitative sample) conservatively comprise nearly 40% of the US population, and more likely slightly over 50%. slightly emphasizing those involved in care or service professions-skills and expertise often underrecognized in technology cultures [57,71].…”

Section: Participantsmentioning

confidence: 99%

A Qualitative Exploration of Perceptions of Algorithmic Fairness

Woodruff

Fox

Rousso-Schindler

et al. 2018

Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

192

113

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Algorithmic systems increasingly shape information people are exposed to as well as influence decisions about employment, finances, and other opportunities. In some cases, algorithmic systems may be more or less favorable to certain groups or individuals, sparking substantial discussion of algorithmic fairness in public policy circles, academia, and the press. We broaden this discussion by exploring how members of potentially affected communities feel about algorithmic fairness. We conducted workshops and interviews with 44 participants from several populations traditionally marginalized by categories of race or class in the United States. While the concept of algorithmic fairness was largely unfamiliar, learning about algorithmic (un)fairness elicited negative feelings that connect to current national discussions about racial injustice and economic inequality. In addition to their concerns about potential harms to themselves and society, participants also indicated that algorithmic fairness (or lack thereof) could substantially affect their trust in a company or product.

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Section: Participantsmentioning

confidence: 99%

A Qualitative Exploration of Perceptions of Algorithmic Fairness

Woodruff

Fox

Rousso-Schindler

et al. 2018

Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

192

113

View full text Add to dashboard Cite

show abstract

“…Additionally, a handful of manuscripts in the a priori and a posteriori umbrella category were influenced by Feminist HCI [11]. These manuscripts were particularly concerned with social justice through research in gender-focused areas using Bardzell's framework: for instance, representing gendered labor on Wikipedia [69], understanding feminist crowd-science [81], and documenting web-design completed primarily by women [39]. There was one manuscript working with Feminist HCI that did not focus [11].…”

Section: Gendermentioning

confidence: 99%

Intersectional HCI

Schlesinger

Edwards

Grinter

2017

Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

289

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Understanding users becomes increasingly complicated when we grapple with various overlapping attributes of an individual's identity. In this paper we introduce intersectionality as a framework for engaging with the complexity of users'-and authors'-identities, and situating these identities in relation to their contextual surroundings. We conducted a meta-review of identity representation in the CHI proceedings, collecting a corpus of 140 manuscripts on gender, ethnicity, race, class, and sexuality published between 1982-2016. Drawing on this corpus, we analyze how identity is constructed and represented in CHI research to examine intersectionality in a human-computer interaction (HCI) context. We find that previous identity-focused research tends to analyze one facet of identity at a time. Further, research on ethnicity and race lags behind research on gender and socioeconomic class. We conclude this paper with recommendations for incorporating intersectionality in HCI research broadly, encouraging clear reporting of context and demographic information, inclusion of author disclosures, and deeper engagement with identity complexities.

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“…About half of the papers are explicit about increasing the problem-solving capacity of researchers or advancing the state of knowledge. For instance, Menking and Erickson [33] studied the work of women on Wikipedia, noting how 'Wikipedia's gender gap may relate to prevailing feeling rules or participation strategies; at the same time this work contributes to advancing Hochschild's theory of emotions work […]' (p. 208). Some papers also describe implications for research methodology [4] and modelling [7,51].…”

Section: Research and Practical Impacts: Equally Commonmentioning

confidence: 99%

HCI Research as Problem-Solving

Oulasvirta

Hornbæk

2016

Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems

114

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This essay contributes a meta-scientific account of humancomputer interaction (HCI) research as problem-solving. We build on the philosophy of Larry Laudan, who develops problem and solution as the foundational concepts of science. We argue that most HCI research is about three main types of problem: empirical, conceptual, and constructive. We elaborate upon Laudan's concept of problem-solving capacity as a universal criterion for determining the progress of solutions (outcomes): Instead of asking whether research is 'valid' or follows the 'right' approach, it urges us to ask how its solutions advance our capacity to solve important problems in human use of computers. This offers a rich, generative, and 'discipline-free' view of HCI and resolves some existing debates about what HCI is or should be. It may also help unify efforts across nominally disparate traditions in empirical research, theory, design, and engineering.

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The Heart Work of Wikipedia

Cited by 83 publications

References 19 publications

A Qualitative Exploration of Perceptions of Algorithmic Fairness

A Qualitative Exploration of Perceptions of Algorithmic Fairness

Intersectional HCI

HCI Research as Problem-Solving

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