Publication statistics

Pub. period:2008-2011
Pub. count:10
Number of co-authors:25



Co-authors

Number of publications with 3 favourite co-authors:

Robert C. Miller:6
David R. Karger:5
Greg Little:2

 

 

Productive colleagues

Michael S. Bernstein's 3 most productive colleagues in number of publications:

Mary Czerwinski:80
Eric Horvitz:70
Mark S. Ackerman:67
 
 
 

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Michael S. Bernstein

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Publications by Michael S. Bernstein (bibliography)

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2011
 
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Marcus, Adam, Bernstein, Michael S., Badar, Osama, Karger, David R., Madden, Samuel and Miller, Robert C. (2011): Twitinfo: aggregating and visualizing microblogs for event exploration. In: Proceedings of ACM CHI 2011 Conference on Human Factors in Computing Systems 2011. pp. 227-236.

Microblogs are a tremendous repository of user-generated content about world events. However, for people trying to understand events by querying services like Twitter, a chronological log of posts makes it very difficult to get a detailed understanding of an event. In this paper, we present TwitInfo, a system for visualizing and summarizing events on Twitter. TwitInfo allows users to browse a large collection of tweets using a timeline-based display that highlights peaks of high tweet activity. A novel streaming algorithm automatically discovers these peaks and labels them meaningfully using text from the tweets. Users can drill down to subevents, and explore further via geolocation, sentiment, and popular URLs. We contribute a recall-normalized aggregate sentiment visualization to produce more honest sentiment overviews. An evaluation of the system revealed that users were able to reconstruct meaningful summaries of events in a small amount of time. An interview with a Pulitzer Prize-winning journalist suggested that the system would be especially useful for understanding a long-running event and for identifying eyewitnesses. Quantitatively, our system can identify 80-100% of manually labeled peaks, facilitating a relatively complete view of each event studied.

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Bernstein, Michael S., Ackerman, Mark S. and Miller, Robert C. (2011): The trouble with social computing systems research. In: Proceedings of ACM CHI 2011 Conference on Human Factors in Computing Systems 2011. pp. 389-398.

Social computing has led to an explosion of research in understanding users, and it has the potential to similarly revolutionize systems research. However, the number of papers designing and building new sociotechnical systems has not kept pace. We analyze challenges facing social computing systems research, ranging from misaligned methodological incentives, evaluation expectations, double standards, and relevance compared to industry. We suggest improvements for the community to consider so that we can chart the future of our field.

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Bernstein, Michael S., Brandt, Joel, Miller, Robert C. and Karger, David R. (2011): Crowds in two seconds: enabling realtime crowd-powered interfaces. In: Proceedings of the 2011 ACM Symposium on User Interface Software and Technology 2011. pp. 33-42.

Interactive systems must respond to user input within seconds. Therefore, to create realtime crowd-powered interfaces, we need to dramatically lower crowd latency. In this paper, we introduce the use of synchronous crowds for on-demand, realtime crowdsourcing. With synchronous crowds, systems can dynamically adapt tasks by leveraging the fact that workers are present at the same time. We develop techniques that recruit synchronous crowds in two seconds and use them to execute complex search tasks in ten seconds. The first technique, the retainer model, pays workers a small wage to wait and respond quickly when asked. We offer empirically derived guidelines for a retainer system that is low-cost and produces on-demand crowds in two seconds. Our second technique, rapid refinement, observes early signs of agreement in synchronous crowds and dynamically narrows the search space to focus on promising directions. This approach produces results that, on average, are of more reliable quality and arrive faster than the fastest crowd member working alone. To explore benefits and limitations of these techniques for interaction, we present three applications: Adrenaline, a crowd-powered camera where workers quickly filter a short video down to the best single moment for a photo; and Puppeteer and A|B, which examine creative generation tasks, communication with workers, and low-latency voting.

© All rights reserved Bernstein et al. and/or ACM Press

2010
 
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Bernstein, Michael S., Marcus, Adam, Karger, David R. and Miller, Robert C. (2010): Enhancing directed content sharing on the web. In: Proceedings of ACM CHI 2010 Conference on Human Factors in Computing Systems 2010. pp. 971-980.

To find interesting, personally relevant web content, people rely on friends and colleagues to pass links along as they encounter them. In this paper, we study and augment link-sharing via e-mail, the most popular means of sharing web content today. Armed with survey data indicating that active sharers of novel web content are often those that actively seek it out, we developed FeedMe, a plug-in for Google Reader that makes directed sharing of content a more salient part of the user experience. FeedMe recommends friends who may be interested in seeing content that the user is viewing, provides information on what the recipient has seen and how many emails they have received recently, and gives recipients the opportunity to provide lightweight feedback when they appreciate shared content. FeedMe introduces a novel design space within mixed-initiative social recommenders: friends who know the user voluntarily vet the material on the user's behalf. We performed a two-week field experiment (N=60) and found that FeedMe made it easier and more enjoyable to share content that recipients appreciated and would not have found otherwise.

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Bernstein, Michael S., Suh, Bongwon, Hong, Lichan, Chen, Jilin, Kairam, Sanjay and Chi, Ed H. (2010): Eddi: interactive topic-based browsing of social status streams. In: Proceedings of the 2010 ACM Symposium on User Interface Software and Technology 2010. pp. 303-312.

Twitter streams are on overload: active users receive hundreds of items per day, and existing interfaces force us to march through a chronologically-ordered morass to find tweets of interest. We present an approach to organizing a user's own feed into coherently clustered trending topics for more directed exploration. Our Twitter client, called Eddi, groups tweets in a user's feed into topics mentioned explicitly or implicitly, which users can then browse for items of interest. To implement this topic clustering, we have developed a novel algorithm for discovering topics in short status updates powered by linguistic syntactic transformation and callouts to a search engine. An algorithm evaluation reveals that search engine callouts outperform other approaches when they employ simple syntactic transformation and backoff strategies. Active Twitter users evaluated Eddi and found it to be a more efficient and enjoyable way to browse an overwhelming status update feed than the standard chronological interface.

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Bernstein, Michael S., Little, Greg, Miller, Robert C., Hartmann, Bjorn, Ackerman, Mark S., Karger, David R., Crowell, David and Panovich, Katrina (2010): Soylent: a word processor with a crowd inside. In: Proceedings of the 2010 ACM Symposium on User Interface Software and Technology 2010. pp. 313-322.

This paper introduces architectural and interaction patterns for integrating crowdsourced human contributions directly into user interfaces. We focus on writing and editing, complex endeavors that span many levels of conceptual and pragmatic activity. Authoring tools offer help with pragmatics, but for higher-level help, writers commonly turn to other people. We thus present Soylent, a word processing interface that enables writers to call on Mechanical Turk workers to shorten, proofread, and otherwise edit parts of their documents on demand. To improve worker quality, we introduce the Find-Fix-Verify crowd programming pattern, which splits tasks into a series of generation and review stages. Evaluation studies demonstrate the feasibility of crowdsourced editing and investigate questions of reliability, cost, wait time, and work time for edits.

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Bernstein, Michael S. (2010): Crowd-powered interfaces. In: Proceedings of the 2010 ACM Symposium on User Interface Software and Technology 2010. pp. 347-350.

We investigate crowd-powered interfaces: interfaces that embed human activity to support high-level conceptual activities such as writing, editing and question-answering. For example, a crowd-powered interface using paid crowd workers can compute a series of textual cuts and edits to a paragraph, then provide the user with an interface to condense his or her writing. We map out the design space of interfaces that depend on outsourced, friendsourced, and data mined resources, and report on designs for each of these. We discuss technical and motivational challenges inherent in human-powered interfaces.

© All rights reserved Bernstein and/or his/her publisher

 
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Bernstein, Michael S., Tan, Desney, Smith, Greg, Czerwinski, Mary and Horvitz, Eric (2010): Personalization via friendsourcing. In ACM Transactions on Computer-Human Interaction, 17 (2) p. 6.

When information is known only to friends in a social network, traditional crowdsourcing mechanisms struggle to motivate a large enough user population and to ensure accuracy of the collected information. We thus introduce friendsourcing, a form of crowdsourcing aimed at collecting accurate information available only to a small, socially-connected group of individuals. Our approach to friendsourcing is to design socially enjoyable interactions that produce the desired information as a side effect. We focus our analysis around Collabio, a novel social tagging game that we developed to encourage friends to tag one another within an online social network. Collabio encourages friends, family, and colleagues to generate useful information about each other. We describe the design space of incentives in social tagging games and evaluate our choices by a combination of usage log analysis and survey data. Data acquired via Collabio is typically accurate and augments tags that could have been found on Facebook or the Web. To complete the arc from data collection to application, we produce a trio of prototype applications to demonstrate how Collabio tags could be utilized: an aggregate tag cloud visualization, a personalized RSS feed, and a question and answer system. The social data powering these applications enables them to address needs previously difficult to support, such as question answering for topics comprehensible only to a few of a user's friends.

© All rights reserved Bernstein et al. and/or ACM Press

2008
 
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Bernstein, Michael S., Shrager, Jeff and Winograd, Terry (2008): Taskpos: exploring fluid boundaries in an associative window visualization. In: Cousins, Steve B. and Beaudouin-Lafon, Michel (eds.) Proceedings of the 21st Annual ACM Symposium on User Interface Software and Technology October 19-22, 2008, Monterey, CA, USA. pp. 231-234.

 
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Miller, Robert C., Chou, Victoria H., Bernstein, Michael S., Little, Greg, Kleek, Max Van, Karger, David R. and Schraefel, M. C. (2008): Inky: a sloppy command line for the web with rich visual feedback. In: Cousins, Steve B. and Beaudouin-Lafon, Michel (eds.) Proceedings of the 21st Annual ACM Symposium on User Interface Software and Technology October 19-22, 2008, Monterey, CA, USA. pp. 131-140.

 
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