Alqassim, Mona

DeVito, Michael A.

Jelen, Ben

Kresnye, Cassie

Maestre, Juan Fernando

Shih, Patrick C.

Siek, Katie A.

Walker, Ashley Marie

Wolters, Maria

Crossref

Asynchronous Remote Communities (ARC) methodology has been used to explore HCI topics in a range of contexts. This innovative methodology takes advantage of the technological tools and platforms that are often the subject of HCI research to extend existing methods of data collection, pushing methodology beyond historical modes and allowing better connection with populations who have previously been left out of the research process. This SIG will make space for researchers and practitioners who are interested in using ARC methodology to connect with people who have already used ARC and discuss challenges and opportunities with this methodology, and how to extend similar kinds of innovative, distributed computing based methods into new contexts.<br/

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     Edinburgh Research Explorer                                      ARC: Moving the Method ForwardCitation for published version:Walker, AM, DeVito, MA, Maestre, JF, Siek, KA, Kresnye, C, Jelen, B, Shih, PC, Wolters, M & Alqassim, M2019, ARC: Moving the Method Forward. in Extended Abstracts of the 2019 CHI Conference on HumanFactors in Computing Systems. CHI EA '19, ACM, New York, NY, USA, pp. SIG06:1-SIG06:4, ACM CHIConference on Human Factors in Computing Systems 2019, Glasgow, United Kingdom, 4/05/19. DOI:10.1145/3290607.3311763Digital Object Identifier (DOI):10.1145/3290607.3311763Link:Link to publication record in Edinburgh Research ExplorerDocument Version:Peer reviewed versionPublished In:Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing SystemsGeneral rightsCopyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s)and / or other copyright owners and it is a condition of accessing these publications that users recognise andabide by the legal requirements associated with these rights.Take down policyThe University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorercontent complies with UK legislation. If you believe that the public display of this file breaches copyright pleasecontact openaccess@ed.ac.uk providing details, and we will remove access to the work immediately andinvestigate your claim.Download date: 21. Jun. 2019ARC: Moving the Method ForwardAshley Marie WalkerMichael A. DeVitoNorthwestern UniversityEvanston, IL, USAamwalker@u.northwestern.edudevitom@u.northwestern.eduJuan Fernando MaestreKatie A. SiekCassie KresnyeBen JelenPatrick C. ShihIndiana University BloomingtonBloomington, IN, USAjmaestre@indiana.eduksiek@indiana.educkresnye@iu.edubcjelen@indiana.edupatshih@indiana.eduMaria WoltersUniversity of EdinburghEdinburgh, Scotland, UKmaria.wolters@ed.ac.ukMona AlqassimUniversity of EdinburghEdinburgh, Scotland, UKmona.alqassim@ed.ac.ukABSTRACTAsynchronous Remote Communities (ARC) methodology has been used to explore HCI topics ina range of contexts. This innovative methodology takes advantage of the technological tools andplatforms that are often the subject of HCI research to extend existing methods of data collection,pushing methodology beyond historical modes and allowing better connection with populations whohave previously been left out of the research process. This SIG will make space for researchers andPermission to make digital or hard copies of part or all of this work for personal or classroom use is granted without feeprovided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and thefull citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contactthe owner/author(s).CHI’19 Extended Abstracts, May 4–9, 2019, Glasgow, Scotland UK© 2019 Copyright held by the owner/author(s).ACM ISBN 978-1-4503-5971-9/19/05.https://doi.org/10.1145/3290607.3311763CHI 2019 SIG  CHI 2019, May 4–9, 2019, Glasgow, Scotland, UKSIG06, Page 1practitioners who are interested in using ARC methodology to connect with people who have alreadyused ARC and discuss challenges and opportunities with this methodology, and how to extend similarkinds of innovative, distributed computing based methods into new contexts.ACM Reference Format:Ashley Marie Walker, Michael A. DeVito, Juan Fernando Maestre, Katie A. Siek, Cassie Kresnye, Ben Jelen, PatrickC. Shih, Maria Wolters, and Mona Alqassim. 2019. ARC: Moving the Method Forward. In CHI Conference onHuman Factors in Computing Systems Extended Abstracts (CHI’19 Extended Abstracts), May 4–9, 2019, Glasgow,Scotland UK. ACM, New York, NY, USA, 4 pages. https://doi.org/10.1145/3290607.3311763INTRODUCTIONIn recent years, the CHI community has begun to investigate and serve the technology-related needsof underserved communities (e.g., [8]). These communities span affinities, ranging from stigmatizedcommunities such as LGBTQ+ and individuals living with HIV, to economically marginalized commu-nities such as low-income individuals in inner cities and rural areas (e.g., [1, 3]), and communitieswith specialized mobility and care needs [6]. However, traditional research methods can sometimespose problems for these communities, ranging from heightened identifiability concerns, causing harm,to simply asking too much of participants in terms of time, travel, or resource.To allow anyone with Internet access to participate in research, MacLeod et al. proposed theAsynchronous Remote Communities (ARC) methodology [4], in which participants join a closed orsecret group on an online social platform, where research prompts are deployed periodically over thelength of a study. The ARC method, which breaks large, time-consuming methods into smaller taskswhile removing the need for physical co-location, has the potential to allow wider participation frommarginalized communities, consequently improving the external validity and inclusivity. Additionally,it can provide options for rapidly adjusting the context of one’s research to fit the community athand, e.g. employing Facebook groups to study communities that already largely exist in these privategroup spaces, while still respecting existing community norms.As an example, consider two scenarios. First, consider a study on low-income individuals andalgorithmic discrimination in criminal justice, one which seeks to evaluate algorithms deployedstatewide in a state with amix of urban, suburban, and rural areas. For the low-income rural participant,driving halfway across the state to a small city with a university for an hour-long interview is a bigask and a single interview may not be ideal for capturing perceptions of subtle biases that unfold overtime. Similarly, consider a project aimed at identifying the needs of nonbinary individuals on socialplatforms, pulling from a population that is small and distributed, and has unique needs regardinganonymity and stigmatization. In this case, ARC allows recruitment from all over the world, andparticipation can happen entirely on one’s own computer. Research activities are masked as simplybrowsing Facebook, without a need to explain trips to a lab to potentially-hostile parties. In bothCHI 2019 SIG  CHI 2019, May 4–9, 2019, Glasgow, Scotland, UKSIG06, Page 2cases, the nature of ARC also potentially provides solidarity and a space for discovering new sourcesof social support for these marginalized populations, divorced from a need for geographic proximity.At the same time, this method is relatively new and not without problems of its own. ARC is beingused by several groups within the HCI community, with each group taking different approaches, usingthe framework for different kinds of questions, and making their own modifications and innovationsto the core idea. This leaves us with a wealth of potential that requires discussion and collaborationto mature for the benefit of the community. ARC method also raises its own questions. Though manybarriers are removed, current ARC approaches still require Internet access, which may be a challengefor some rural populations [10] and potentially exclude older and younger participants who may beaffected by differing levels of digital skills and access divide among these groups [9]. Additionally,in being user-friendly, ARC relies on existing social media platforms for infrastructure. While thisdoes make for less work on the participant’s part, it also introduces a wealth of privacy, ownership,and ethics concerns for researchers, as social platforms are increasingly revealed to be grappling withtheir own data and ethics issues [10]. These issues would be best addressed by the community as awhole, and not one-off decisions between a researcher and their local ethics review board.ARCs have the potential to solve practical research problems, make researchers more aware ofand responsive to the needs and constraints of participants, thus de-colonializing our research, andproviding wellbeing benefits to participants themselves. This approach has been refined recently [5],but is still early on in its development as an HCI method. In this SIG, we will gather researchers whoare currently or plan to use ARC in HCI research, including the originator of the method, to sharebest practices, and co-create an agenda for expanding the method, and for addressing the key ethicaland practical challenges the method involves. We hope to provide a space for researchers to discoverand explore this methodology, and take part in furthering it.MOTIVATION AND TIMELINESSCHI 2019 is the ideal venue for a SIG on ARC and related methodologies. ARC itself can be consideredan up-and-coming method in HCI, and was recently spotlighted by a case study at CHI in 2019,empirical work at CHI 2017 [4, 6], and a methods paper at CHI 2018 [5]. ARC also provides apossible solution to key problems in areas that are of increasing interest to the larger HCI community.Recent calls for more intersectional work focused on marginalized communities (e.g., [7]) require newapproaches that respect and adapt to the needs of these communities. Similarly, recent calls for morediverse samples that go beyond the college campus or the immediate community, require methodsthat can cross borders and time zones, a major strength of this asynchronous, distributed method.Finally, as we broaden the types of data we collect in the face of new restrictions on and questionsabout the utility of trace data for examining behavior [2], ARC provides a flexible framework in whichCHI 2019 SIG  CHI 2019, May 4–9, 2019, Glasgow, Scotland, UKSIG06, Page 3to try novel exercises in a lightweight and non-intrusive manner, potentially allowing researchers toexperiment with pushing the boundaries of their own data collection practices.We propose holding this SIG at CHI 2019 as a potential answer to many of the methodological issuesthat have been raised over the last few conference cycles, and as a space to encourage and enablediscussions about how to innovate moving forward. We can, as a group, find ways to constructivelyaddress known issues such as differential Internet skills and access, analysis and triangulation ofgreat amounts of data coming from different activities and instruments, and the platform-boundednature of the method itself. By welcoming participants who are new to ARC, we can educate whilebringing in new voices and fresh ideas that may help us see new ways forward, potential solutions,and even new contexts in which to apply ARC.REFERENCES[1] Tawanna R Dillahunt, Sheena Erete, Roxana Galusca, Aarti Israni, Denise Nacu, and Phoebe Sengers. 2017. Reflectionson Design Methods for Underserved Communities. In Companion of the 2017 ACM Conference on Computer SupportedCooperative Work and Social Computing. ACM, 409–413.[2] Nicole B Ellison, Megan French, Eden Litt, S Shyam Sundar, and Penny Trieu. 2018. Without a Trace: How StudyingInvisible Interactions Can Help Us Understand Social Media. In Companion of the 2018 ACM Conference on ComputerSupported Cooperative Work and Social Computing. ACM, 129–132.[3] Jean Hardy and Silvia Lindtner. 2017. Constructing a desiring user: Discourse, rurality, and design in location-based socialnetworks. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing.ACM, 13–25.[4] Haley MacLeod, Ben Jelen, Annu Prabhakar, Lora Oehlberg, Katie A Siek, and Kay Connelly. 2016. Lessons learned fromconducting group-based research on facebook. In Proceedings of the 2016 CHI Conference Extended Abstracts on HumanFactors in Computing Systems. ACM, 804–815.[5] Juan F Maestre, Haley MacLeod, Ciabhan L Connelly, Julia C Dunbar, Jordan Beck, Katie A Siek, and Patrick C Shih. 2018.Defining through expansion: conducting asynchronous remote communities (arc) research with stigmatized groups. InProceedings of the 2018 CHI Conference on Human Factors in Computing Systems. ACM, 557.[6] Annu Sible Prabhakar, Lucia Guerra-Reyes, Vanessa M Kleinschmidt, Ben Jelen, Haley MacLeod, Kay Connelly, andKatie A Siek. 2017. Investigating the suitability of the asynchronous, remote, community-based method for pregnant andnew mothers. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM, 4924–4934.[7] Ari Schlesinger, W Keith Edwards, and Rebecca E Grinter. 2017. Intersectional HCI: Engaging identity through gender,race, and class. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM, 5412–5427.[8] Angelika Strohmayer, Mary Laing, and Rob Comber. 2017. Technologies and Social Justice Outcomes in SexWork Charities:Fighting Stigma, Saving Lives. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM,3352–3364.[9] Rebecca P Yu, Nicole B Ellison, Ryan J McCammon, and Kenneth M Langa. 2016. Mapping the two levels of digital divide:Internet access and social network site adoption among older adults in the USA. Information, Communication & Society19, 10 (2016), 1445–1464.[10] J Zunger. 2018. Computer science faces an ethics crisis. The Cambridge Analytica scandal proves it. Boston Globe 22(2018).CHI 2019 SIG  CHI 2019, May 4–9, 2019, Glasgow, Scotland, UKSIG06, Page 4

ARC: Moving the Method Forward

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ARC: Moving the Method Forward

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