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Dive into the research topics where Casey Fiesler is active.

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Featured researches published by Casey Fiesler.


Interacting with Computers | 2011

Domestic violence and information communication technologies

Jill P. Dimond; Casey Fiesler; Amy Bruckman

Physical violence against women is pervasive through out the world and domestic violence has been a longstanding issue in feminist activism and research. Yet, these experiences are often not represented in technological research or design. In the move to consider HCI at the margins, in this paper, we ask: how have ICTs affected the experiences of domestic violence survivors? We interviewed female survivors living in a domestic violence shelter about their experiences with technology. Participants reported that they were harassed with mobile phones, experienced additional harassment (but also support) via social networking sites, and tried to resist using their knowledge of security and privacy.


conference on computer supported cooperative work | 2014

Remixers' understandings of fair use online

Casey Fiesler; Amy Bruckman

How do online content creators make decisions about copyright law? In the course of day-to-day online activities, Internet users are forced to make subtle judgments about one of the most confusing and nuanced areas of law, copyright and fair use. In this study, we conducted semi-structured interviews with eleven content creators who participate in remix and fan creation activities online, to try to probe their legal understandings and attitudes. We found that social norms that emerge among these content creators do not always track to what the law actually says, but are often guided more by ethical concerns. Our participants showed surprisingly similar patterns of understandings and confusions, impacting technology use and interaction online.


human factors in computing systems | 2016

An Archive of Their Own: A Case Study of Feminist HCI and Values in Design

Casey Fiesler; Shannon Morrison; Amy Bruckman

Rarely are computing systems developed entirely by members of the communities they serve, particularly when that community is underrepresented in computing. Archive of Our Own (AO3), a fan fiction archive with nearly 750,000 users and over 2 million individual works, was designed and coded primarily by women to meet the needs of the online fandom community. Their design decisions were informed by existing values and norms around issues such as accessibility, inclusivity, and identity. We conducted interviews with 28 users and developers, and with this data we detail the history and design of AO3 using the framework of feminist HCI and focusing on the successful incorporation of values into design. We conclude with considering examples of complexity in values in design work: the use of design to mitigate tensions in values and to influence value formation or change.


conference on computer supported cooperative work | 2016

Reality and Perception of Copyright Terms of Service for Online Content Creation

Casey Fiesler; Cliff Lampe; Amy Bruckman

From amateur creativity to social media status updates, nearly every Internet user is also a content creator-but who owns that content? Policy, including intellectual property rights, is a necessary but often invisible part of online content sharing and social computing environments. We analyzed the copyright licenses contained in the Terms of Service of 30 different websites where users contribute content, then conducted a survey to match perceptions of copyright terms to the reality. We found that licensing terms vary in unpredictable ways, and that user expectations and opinions differ by license and by type of website. Moreover, the most undesirable terms, such as right to modify, appear more frequently than users expect. We argue that users care about how their content can be used yet lack critical information. Site designers should take user needs and community norms into account in creating and explaining copyright policies.


international conference on supporting group work | 2012

Qualitative data collection technologies: a comparison of instant messaging, email, and phone

Jill P. Dimond; Casey Fiesler; Betsy James DiSalvo; Jon Pelc; Amy Bruckman

With the growing body of qualitative research on HCI and social computing, it is natural that researchers may choose to conduct that research in a mediated fashion - over telephone or computer networks. In this paper we compare three different qualitative data collection technologies: phone, instant message (IM), and email. We use quantitative analysis techniques to examine the differences between the methods specifically concerning word count and qualitative codes. We find that there are differences between the methods, and that each technology has affordances that impact the data. Although phone interviews contain four times as many words on average as email and IM, we were surprised to discover that there is no significant difference in number of unique qualitative codes expressed between phone and IM.


human factors in computing systems | 2006

Managing Deviant Behavior in Online Communities III

Amy Bruckman; Jennifer E. Below; Lucas Gill Dixon; Casey Fiesler; Eric Gilbert; Sarah A. Gilbert; J. Nathan Matias

Wherever groups of people gather, norms for appropriate behavior emerge, and some people chose to violate those norms. What is an exercise of free speech to one person, to another is disruptive, harassing, racist, or worse. For groups that communicate online, a range of technical and social mechanisms are available to help create a climate conducive to meeting the groups stated mission. How do designers of online systems decide what kind of conduct is acceptable? How are these expectations communicated to members? How can designers help prevent and manage deviant behavior? What are the implications of corporate control of content for ideals of free expression? This panel brings together experts from media theory, computer-supported collaborative learning (CSCL), computer-supported cooperative work (CSCW), and online entertainment to explore current issues in this complex research area.


conference on computer supported cooperative work | 2015

Understanding Copyright Law in Online Creative Communities

Casey Fiesler; Jessica L. Feuston; Amy Bruckman

Copyright law is increasingly relevant to everyday interactions online, from social media status updates to artists showcasing their work. This is especially true in creative spaces where rules about reuse and remix are notoriously gray. Based on a content analysis of public forum postings in eight different online communities featuring different media types (music, video, art, and writing), we found that copyright is a frequent topic of conversation and that much of this discourse stems from problems that copyright causes for creative activities. We identify the major types of problems encountered, including chilling effects that negatively impact technology use. We find that many challenges can be explained by lack of knowledge about legal or policy rules, including breakdowns in user expectations for the sites they use. We argue that lack of clarity is a pervasive usability problem that should be considered more carefully in the design of user-generated content platforms.


human factors in computing systems | 2014

Copyright terms in online creative communities

Casey Fiesler; Amy Bruckman

A key usability problem for websites is the complexity of their terms and conditions. Within the HCI community, attention to this issue to date has primarily focused on privacy policies. We begin to build on this work, extending it to copyright terms. With so many people posting everything from status updates to digital art online, intellectual property rights are increasingly important to the end user. We conducted a content analysis of 30 different websites where users can share creative work, focusing on the licenses and usage rights that users grant to those websites. Due to difficult readability, legalese, and a lack of plain language explanations, it is likely that users may not know what rights they are granting. Next steps include a user survey to determine whether this is the case, and further exploration of the impact on usability.


international conference on supporting group work | 2016

Characterizations of Online Harassment: Comparing Policies Across Social Media Platforms

Jessica Pater; Moon K. Kim; Elizabeth D. Mynatt; Casey Fiesler

Harassment in online spaces is increasingly part of public debate and concern. Pervasive problems like cyberbullying, hate speech, and the glorification of self-harm have highlighted the breadth and depth of harassment taking place online. In this study we conduct a content analysis of the governing policies for fifteen social media platforms as they relate to harassment (of oneself and/or of community members) and other associated behaviors. We find that there is a striking inconsistency in how platform-specific policies depict harassment. Additionally, how these policies prescribe responses to harassment vary from mild censuring to the involvement of law enforcement. Finally, based on our analysis and findings, we discuss the potential for harnessing the power of the online communities to create norms around problematic behaviors.


conference on computer supported cooperative work | 2017

What (or Who) Is Public?: Privacy Settings and Social Media Content Sharing

Casey Fiesler; Michaelanne Dye; Jessica L. Feuston; Chaya Hiruncharoenvate; Clayton J. Hutto; Shannon Morrison; Parisa Khanipour Roshan; Umashanthi Pavalanathan; Amy Bruckman; Munmun De Choudhury; Eric Gilbert

When social networking sites give users granular control over their privacy settings, the result is that some content across the site is public and some is not. How might this content--or characteristics of users who post publicly versus to a limited audience--be different? If these differences exist, research studies of public content could potentially be introducing systematic bias. Via Mechanical Turk, we asked 1,815 Facebook users to share recent posts. Using qualitative coding and quantitative measures, we characterize and categorize the nature of the content. Using machine learning techniques, we analyze patterns of choices for privacy settings. Contrary to expectations, we find that content type is not a significant predictor of privacy setting; however, some demographics such as gender and age are predictive. Additionally, with consent of participants, we provide a dataset of nearly 9,000 public and non-public Facebook posts.

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Amy Bruckman

Georgia Institute of Technology

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Jessica Pater

Georgia Institute of Technology

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Michael Skirpan

University of Colorado Boulder

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Pamela J. Wisniewski

University of Central Florida

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Allan Baumer

Georgia Institute of Technology

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Brian Magerko

Georgia Institute of Technology

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