Publication statistics

Pub. period:1999-2012
Pub. count:17
Number of co-authors:31



Co-authors

Number of publications with 3 favourite co-authors:

Jaime Teevan:4
Susan Dumais:2
Lada A. Adamic:2

 

 

Productive colleagues

Eytan Adar's 3 most productive colleagues in number of publications:

Susan Dumais:74
James Fogarty:35
Jaime Teevan:30
 
 
 

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Eytan Adar

 

Publications by Eytan Adar (bibliography)

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2012
 
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Mazzia, Alessandra, LeFevre, Kristen and Adar, Eytan (2012): The PViz comprehension tool for social network privacy settings. In: Proceedings of the 2012 Symposium on Usable Privacy and Security 2012. p. 13. Available online

Users' mental models of privacy and visibility in social networks often involve subgroups within their local networks of friends. Many social networking sites have begun building interfaces to support grouping, like Facebook's lists and "Smart Lists," and Google+'s "Circles." However, existing policy comprehension tools, such as Facebook's Audience View, are not aligned with this mental model. In this paper, we introduce PViz, an interface and system that corresponds more directly with how users model groups and privacy policies applied to their networks. PViz allows the user to understand the visibility of her profile according to automatically-constructed, natural sub-groupings of friends, and at different levels of granularity. Because the user must be able to identify and distinguish automatically-constructed groups, we also address the important sub-problem of producing effective group labels. We conducted an extensive user study comparing PViz to current policy comprehension tools (Facebook's Audience View and Custom Settings page). Our study revealed that PViz was comparable to Audience View for simple tasks, and provided a significant improvement for complex, group-based tasks, despite requiring users to adapt to a new tool. Utilizing feedback from the user study, we further iterated on our design, constructing PViz 2.0, and conducted a follow-up study to evaluate our refinements.

© All rights reserved Mazzia et al. and/or their publisher

 
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Laput, Gierad, Adar, Eytan, Dontcheva, Mira and Li, Wilmot (2012): Tutorial-based interfaces for cloud-enabled applications. In: Proceedings of the 2012 ACM Symposium on User Interface Software and Technology 2012. pp. 113-122. Available online

Powerful image editing software like Adobe Photoshop and GIMP have complex interfaces that can be hard to master. To help users perform image editing tasks, we introduce tutorial-based applications (tapps) that retain the step-by-step structure and descriptive text of tutorials but can also automatically apply tutorial steps to new images. Thus, tapps can be used to batch process many images automatically, similar to traditional macros. Tapps also support interactive exploration of parameters, automatic variations, and direct manipulation (e.g., selection, brushing). Another key feature of tapps is that they execute on remote instances of Photoshop, which allows users to edit their images on any Web-enabled device. We demonstrate a working prototype system called TappCloud for creating, managing and using tapps. Initial user feedback indicates support for both the interactive features of tapps and their ability to automate image editing. We conclude with a discussion of approaches and challenges of pushing monolithic direct-manipulation GUIs to the cloud.

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

2011
 
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Hullman, Jessica, Adar, Eytan and Shah, Priti (2011): The impact of social information on visual judgments. In: Proceedings of ACM CHI 2011 Conference on Human Factors in Computing Systems 2011. pp. 1461-1470. Available online

Social visualization systems have emerged to support collective intelligence-driven analysis of a growing influx of open data. As with many other online systems, social signals (e.g., forums, polls) are commonly integrated to drive use. Unfortunately, the same social features that can provide rapid, high-accuracy analysis are coupled with the pitfalls of any social system. Through an experiment involving over 300 subjects, we address how social information signals (social proof) affect quantitative judgments in the context of graphical perception. We identify how unbiased social signals lead to fewer errors over non-social settings and conversely, how biased signals lead to more errors. We further reflect on how systematic bias nullifies certain collective intelligence benefits, and we provide evidence of the formation of information cascades. We describe how these findings can be applied to collaborative visualization systems to produce more accurate individual interpretations in social contexts.

© All rights reserved Hullman et al. and/or their publisher

2009
 
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Adar, Eytan, Teevan, Jaime and Dumais, Susan (2009): Resonance on the web: web dynamics and revisitation patterns. In: Proceedings of ACM CHI 2009 Conference on Human Factors in Computing Systems 2009. pp. 1381-1390. Available online

The Web is a dynamic, ever-changing collection of information accessed in a dynamic way. This paper explores the relationship between Web page content change (obtained from an hourly crawl of over 40K pages) and people's revisitation to those pages (collected via a large scale log analysis of 2.3M users). We identify the relationship, or resonance, between revisitation behavior and the amount and type of changes on those pages. By coupling our large scale log analysis with a complementary user study we explore the intent behind the revisitation behavior we observed. Using the notion of resonance to identify the likely content of interest, we describe a number of ways interaction with changing and revisited information can be better supported. We illustrate how understanding the association between change and revisitation might improve browser, crawler, and search engine design, and present a specific example of how knowledge of both can enable relevant content to be highlighted.

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

2008
 
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Adar, Eytan, Teevan, Jaime and Dumais, Susan (2008): Large scale analysis of web revisitation patterns. In: Proceedings of ACM CHI 2008 Conference on Human Factors in Computing Systems April 5-10, 2008. pp. 1197-1206. Available online

Our work examines Web revisitation patterns. Everybody revisits Web pages, but their reasons for doing so can differ depending on the particular Web page, their topic of interest, and their intent. To characterize how people revisit Web content, we analyzed five weeks of Web interaction logs of over 612,000 users. We supplemented these findings by a survey intended to identify the intent behind the observed revisitation. Our analysis reveals four primary revisitation patterns, each with unique behavioral, content, and structural characteristics. Through our analysis we illustrate how understanding revisitation patterns can enable Web sites to provide improved navigation, Web browsers to predict users' destinations, and search engines to better support fast, fresh, and effective finding and re-finding.

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

 
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Adar, Eytan, Dontcheva, Mira, Fogarty, James and Weld, Daniel S. (2008): Zoetrope: interacting with the ephemeral web. 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. 239-248. Available online

2007
 
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Adar, Eytan, Weld, Daniel S., Bershad, Brian N. and Gribble, Steven S. (2007): Why we search: visualizing and predicting user behavior. In: Proceedings of the 2007 International Conference on the World Wide Web 2007. pp. 161-170. Available online

The aggregation and comparison of behavioral patterns on the WWW represent a tremendous opportunity for understanding past behaviors and predicting future behaviors. In this paper, we take a first step at achieving this goal. We present a large scale study correlating the behaviors of Internet users on multiple systems ranging in size from 27 million queries to 14 million blog posts to 20,000 news articles. We formalize a model for events in these time-varying datasets and study their correlation. We have created an interface for analyzing the datasets, which includes a novel visual artifact, the DTWRadar, for summarizing differences between time series. Using our tool we identify a number of behavioral properties that allow us to understand the predictive power of patterns of use.

© All rights reserved Adar et al. and/or International World Wide Web Conference Committee

 
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Teevan, Jaime, Adar, Eytan, Jones, Rosie and Potts, Michael A. S. (2007): Information re-retrieval: repeat queries in Yahoo's logs. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2007. pp. 151-158. Available online

People often repeat Web searches, both to find new information on topics they have previously explored and to re-find information they have seen in the past. The query associated with a repeat search may differ from the initial query but can nonetheless lead to clicks on the same results. This paper explores repeat search behavior through the analysis of a one-year Web query log of 114 anonymous users and a separate controlled survey of an additional 119 volunteers. Our study demonstrates that as many as 40% of all queries are re-finding queries. Re-finding appears to be an important behavior for search engines to explicitly support, and we explore how this can be done. We demonstrate that changes to search engine results can hinder re-finding, and provide a way to automatically detect repeat searches and predict repeat clicks.

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

2006
 
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Adar, Eytan (2006): GUESS: a language and interface for graph exploration. In: Proceedings of ACM CHI 2006 Conference on Human Factors in Computing Systems 2006. pp. 791-800. Available online

As graph models are applied to more widely varying fields, researchers struggle with tools for exploring and analyzing these structures. We describe GUESS, a novel system for graph exploration that combines an interpreted language with a graphical front end that allows researchers to rapidly prototype and deploy new visualizations. GUESS also contains a novel, interactive interpreter that connects the language and interface in a way that facilities exploratory visualization tasks. Our language, Gython, is a domain-specific embedded language which provides all the advantages of Python with new, graph specific operators, primitives, and shortcuts. We highlight key aspects of the system in the context of a large user survey and specific, real-world, case studies ranging from social and knowledge networks to distributed computer network analysis.

© All rights reserved Adar and/or ACM Press

 
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Teevan, Jaime, Adar, Eytan, Jones, Rosie and Potts, Michael (2006): History repeats itself: repeat queries in Yahoo's logs. In: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2006. pp. 703-704. Available online

Thanks to the ubiquity of the Internet search engine search box, users have come to depend on search engines both to find and re-find information. However, re-finding behavior has not been significantly addressed. Here we look at re-finding queries issued to the Yahoo! search engine by 114 users over a year.

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

2005
 
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Adar, Eytan and Adamic, Lada A. (2005): Tracking Information Epidemics in Blogspace. In: Skowron, Andrzej, Agrawal, Rakesh, Luck, Michael, Yamaguchi, Takahira, Morizet-Mahoudeaux, Pierre, Liu, Jiming and Zhong, Ning (eds.) 2005 IEEE / WIC / ACM International Conference on Web Intelligence WI 2005 19-22 September, 2005, Compiegne, France. pp. 207-214. Available online

2003
 
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Adamic, Lada A., Buyukkokten, Orkut and Adar, Eytan (2003): A social network caught in the Web. In First Monday, 8 (6) . Available online

 
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Lukose, Rajan M., Adar, Eytan, Tyler, Joshua R. and Sengupta, Caesar (2003): SHOCK: communicating with computational messages and automatic private profiles. In: Proceedings of the 2003 International Conference on the World Wide Web 2003. pp. 291-300. Available online

A computationally enhanced message contains some embedded programmatic components that are interpreted and executed automatically upon receipt. Unlike ordinary text email or instant messages, they make possible a number of useful applications. In this paper, we describe a general and flexible messaging system called SHOCK that extends the functionality of prior computational email systems by allowing XML-encoded SHOCK messages to interact with an automatically created profile of a user. These profiles consist of information about the most common tasks users perform, such as their Web browsing behavior, their conventional email usage, etc. Since users are sensitive about such data, the system is designed with privacy as a central design goal, and employs a distributed peer-to-peer architecture to achieve it. The system is largely implemented with commodity Web technologies and provides both a Web interface as well as one that is tightly integrated with users ordinary email clients. With SHOCK, users can send highly targeted messages without violating others privacy, and engage in structured conversation appropriate to the context without disrupting their existing work practices. We describe our implementation in detail, the most useful novel applications of the system, and our experiences with the system in a pilot field test.

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

2002
 
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Pitkow, James E., Schtze, Hinrich, Cass, Todd A., Cooley, Robert, Turnbull, Don, Edmonds, Andy, Adar, Eytan and Breuel, Thomas M. (2002): Personalized search. In Communications of the ACM, 45 (9) pp. 50-55. Available online

2001
 
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Adar, Eytan and Huberman, Bernardo A. (2001): A Market for Secrets. In First Monday, 6 (8) . Available online

2000
 
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Adar, Eytan and Huberman, Bernardo A. (2000): Free Riding on Gnutella. In First Monday, 5 (10) . Available online

1999
 
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Adar, Eytan, Karger, David R. and Stein, Lynn Andrea (1999): Haystack: Per-User Information Environments. In: Proceedings of the 1999 ACM CIKM International Conference on Information and Knowledge Management November 2-6, 1999, Kansas City, Missouri, USA. pp. 413-422. Available online

 
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