Yun Huang

Flying Eyes and Hidden Controllers: A Qualitative Study of People’s Privacy Perceptions of Civilian Drones in The US

Abstract Drones are unmanned aircraft controlled remotely or operated autonomously. While the extant literature suggests that drones can in principle invade people’s privacy, little is known about how people actually think about drones. Drawing from a series of in-depth interviews conducted in the United States, we provide a novel and rich account of people’s privacy perceptions of drones for civilian uses both in general and under specific usage scenarios. Our informants raised both physical and information privacy issues against government, organization and individual use of drones. Informants’ reasoning about the acceptance of drone use was in part based on whether the drone is operating in a public or private space. However, our informants differed significantly in their definitions of public and private spaces. While our informants’ privacy concerns such as surveillance, data collection and sharing have been raised for other tracking technologies such as camera phones and closed-circuit television (CCTV), our interviews highlight two heightened issues of drones: (1) powerful yet inconspicuous data collection, (2) hidden and inaccessible drone controllers. These two aspects of drones render some of people’s existing privacy practices futile (e.g., notice recording and ask controllers to stop or delete the recording). Some informants demanded notifications of drones near them and expected drone controllers asking for their explicit permissions before recording. We discuss implications for future privacy-enhancing drone designs.

CAN: composable accessibility infrastructure via data-driven crowdsourcing

Despite persistent effort, many web pages are still not accessible to everyone. Fixing web accessibility problems can be complicated. Developers need to have extensive knowledge not only of possible accessibility problems but also of approaches for fixing them. This paper is about using the large number of accessibility issues on real websites and crowd-sourced fixes for them as a unique source of learning materials for web developers to learn how to build accessible components in a cost-efficient manner. In this paper, we present the design, development and study of CAN (Composable Accessibility Infrastructure), a crowdsourcing infrastructure that collects web accessibility issues and their fixes, dynamically composes solutions on-the-fly, and delivers the crowd-sourced content as teaching materials. Our unique CAN user interaction and system design enables end users with disabilities to both benefit from and contribute to the system without additional effort in their daily web browsing, and allows web developers to experience real accessibility issues and initiate a learning process with first-hand materials. CAN also provides an opportunity for data-driven discovery of the common implementation practices that cause accessibility issues. We show how CAN addresses a set of accessibility issues on the top 100 popular websites. We also present our user study results where web developers who had varying knowledge of web accessibility all found our system an effective and interesting platform to learning web accessibility.

Understanding Danmaku's Potential in Online Video Learning

Danmaku is a video comment feature which is used to overlay comments onto videos of many types and is gaining popularity in China. In this paper, we explore Danmakus potential in online video learning. We present our survey results of 213 Chinese online users regarding their usage of danmaku. We also propose a new design in which danmaku is modified and leveraged to better facilitate user engagement and interaction in an online learning environment. Our results show that participants perceived both designs to have many benefits in terms of social presence and cognitive presence. Most of the participants post danmaku themselves instead of simply watching others danmaku. In addition, about 40% of the participants who did not prefer the original design showed more positive feedback in the new design.

Examining Twitter Mentions Between Police Agencies and Public Users through the Lens of Stakeholder Theory

Police agencies increasingly leverage social media for community policing. This paper examines how municipal police agencies and public users interact on social media by examining their mentioning behaviors on Twitter. We manually annotated 7,142 tweets sent by 14 municipal police agencies within 6 months in 2015, and classified 15,785 tweets where public users mentioned the agencies. Through the lens of Stakeholder Theory, we also classified 10,956 Twitter users, who either mentioned the agencies or were mentioned by the agencies, into different stakeholder groups. Using both qualitative and quantitative methods, we identified patterns of how they mentioned each other. For example, agencies mentioned more popular and local stakeholders, while less popular and non-local stakeholders sent more negative tweets. We discuss implications of the results for police agencies, which include how to better identify and engage stakeholders and foster community policing on Twitter.

The joy of being a book: benefits of participation in the human library

Human libraries are events intended to provide readers with access to the knowledge and lived experiences of their fellow community members. These events are growing in popularity worldwide, and while often hosted by traditional libraries, can take place in a variety of community organization settings. Human library events depend on the services of the “human books” who volunteer to participate, though recruitment of these volunteers remains one of the most challenging aspects of hosting the events. Previous work has shown that human books enjoy participation in these events, though the specific benefits of human libraries for the human books have not been explored. In this study, we analyze the post‐event survey responses of human books from four different human library events hosted by various institutions. Participants reported a variety of benefits ranging from altruistic to more self‐focused. Reviewing their responses, we suggest eight major categories of benefits for human books. Findings hold implications for effectively recruiting and motivating potential human books, as well as how host institutions may adapt human libraries to the needs of their communities.

Understanding Interactions Between Municipal Police Departments and the Public on Twitter

Law enforcement agencies have started using social media for building community policing, i.e., establishing collaborations between the people in a community and local police departments. Both researchers and practitioners need to understand how the two parties interact on social media on a daily basis, such that effective strategies or tools can be developed for the agencies to better leverage the platforms to fulfill their missions. In this paper, we collected 9,837 tweets from 16 municipal police department official Twitter accounts within 6 months in 2015 and annotated them into different strategies and topics. We further examined the association between tweet features (e.g., hashtags, mentions, content) and user interactions (favorites and retweets) by using regression models. The models reveal surprising findings, e.g., that the number of mentions has a negative correlation with favorites. Our findings provide insights into how to improve interactions between the two parties.

Our Privacy Needs to be Protected at All Costs: Crowd Workers' Privacy Experiences on Amazon Mechanical Turk

Crowdsourcing platforms such as Amazon Mechanical Turk (MTurk) are widely used by organizations, researchers, and individuals to outsource a broad range of tasks to crowd workers. Prior research has shown that crowdsourcing can pose privacy risks (e.g., de-anonymization) to crowd workers. However, little is known about the specific privacy issues crowd workers have experienced and how they perceive the state of privacy in crowdsourcing. In this paper, we present results from an online survey of 435 MTurk crowd workers from the US, India, and other countries and areas. Our respondents reported different types of privacy concerns (e.g., data aggregation, profiling, scams), experiences of privacy losses (e.g., phishing, malware, stalking, targeted ads), and privacy expectations on MTurk (e.g., screening tasks). Respondents from multiple countries and areas reported experiences with the same privacy issues, suggesting that these problems may be endemic to the whole MTurk platform. We discuss challenges, high-level principles and concrete suggestions in protecting crowd workers; privacy on MTurk and in crowdsourcing more broadly.

Examining Q&A of Peer Tutor Learning via Online Videos

Peer tutor learning has been effectively adopted in various learning contexts. It draws attention from the CHI community as it has the potential to be advanced through computer-mediated online video technologies. In this paper, we focus on understanding how Q&A (questions and answers) between tutors and their students is used to promote learning using online videos. Building upon our prior work, we designed and implemented a new Q&A interaction. Through conducting a field study and a follow-up survey of 47 graduate students, our research reveals gaps between a peer tutors strategy (i.e., question position and knowledge type) and a learners preference and answering effort. For example, compared to tutors, learners preferred that questions be inserted in the middle of the videos and that the answers to tacit knowledge-related questions be more numerous and longer than those for explicit knowledge-related questions. The design implications from our findings need to be incorporated into practice and into future research of online videos for peer tutor learning.

Examining conversations between police agencies and the public on Facebook

Social media has emerged to be a new platform for facilitating collaboration between police agencies and the public. However, police agencies still fall short in determining the tactics and strategies to interact with the public in an effective manner. Our work focuses on analyzing conversations between police agencies and the public on Facebook. More specifically, we studied the contents of the agencies posts, how the public commented on these posts, and further, how agencies responded to the publics comments. We generated code-schemes for categorizing the publics comments and the replies of police agencies to them. We further conducted both quantitative and qualitative analyses to understand patterns of their conversations on Facebook. Our findings suggest several practical implications for police agencies to improve their services via social media.

Human Library: Understanding Experience Sharing for Community Knowledge Building

The human library is an event intended to engage members of the community in sharing and learning from each others experiences, and is growing in popularity internationally. Human libraries fall within the larger scope of community knowledge sharing but have received little study and remain largely unsupported by technology. In this study, we examine how community libraries organize and host these events. We present how libraries have attempted to utilize technologies and leverage community support to enable human library events. Our findings reveal inconsistencies in the purpose of human library events, as well as technology applications that are not sufficient to support fully collaborative community knowledge building. We highlight opportunities for increased community participation and technological innovation and also suggest a broader consideration of computer-supported collaborative work in the context of human libraries and experience sharing.