Publication statistics

Pub. period:2009-2012
Pub. count:7
Number of co-authors:10



Co-authors

Number of publications with 3 favourite co-authors:

Jennifer Mankoff:4
Scott E. Hudson:3
Scott Counts:1

 

 

Productive colleagues

Julia Schwarz's 3 most productive colleagues in number of publications:

Scott E. Hudson:113
Jennifer Mankoff:45
Meredith Ringel Mo..:38
 
 
 

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Julia Schwarz

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Publications by Julia Schwarz (bibliography)

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2012
 
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Morris, Meredith Ringel, Counts, Scott, Roseway, Asta, Hoff, Aaron and Schwarz, Julia (2012): Tweeting is believing?: understanding microblog credibility perceptions. In: Proceedings of ACM CSCW12 Conference on Computer-Supported Cooperative Work 2012. pp. 441-450.

Twitter is now used to distribute substantive content such as breaking news, increasing the importance of assessing the credibility of tweets. As users increasingly access tweets through search, they have less information on which to base credibility judgments as compared to consuming content from direct social network connections. We present survey results regarding users' perceptions of tweet credibility. We find a disparity between features users consider relevant to credibility assessment and those currently revealed by search engines. We then conducted two experiments in which we systematically manipulated several features of tweets to assess their impact on credibility ratings. We show that users are poor judges of truthfulness based on content alone, and instead are influenced by heuristics such as user name when making credibility assessments. Based on these findings, we discuss strategies tweet authors can use to enhance their credibility with readers (and strategies astute readers should be aware of!). We propose design improvements for displaying social search results so as to better convey credibility.

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

2011
 
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Schwarz, Julia and Morris, Meredith (2011): Augmenting web pages and search results to support credibility assessment. In: Proceedings of ACM CHI 2011 Conference on Human Factors in Computing Systems 2011. pp. 1245-1254.

The presence (and, sometimes, prominence) of incorrect and misleading content on the Web can have serious consequences for people who increasingly rely on the internet as their information source for topics such as health, politics, and financial advice. In this paper, we identify and collect several page features (such as popularity among specialized user groups) that are currently difficult or impossible for end users to assess, yet provide valuable signals regarding credibility. We then present visualizations designed to augment search results and Web pages with the most promising of these features. Our lab evaluation finds that our augmented search results are particularly effective at increasing the accuracy of users'" credibility assessments, highlighting the potential of data aggregation and simple interventions to help people make more informed decisions as they search for information online.

© All rights reserved Schwarz and Morris and/or their publisher

 
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Schwarz, Julia, Mankoff, Jennifer and Hudson, Scott E. (2011): Monte Carlo methods for managing interactive state, action and feedback under uncertainty. In: Proceedings of the 2011 ACM Symposium on User Interface Software and Technology 2011. pp. 235-244.

Current input handling systems provide effective techniques for modeling, tracking, interpreting, and acting on user input. However, new interaction technologies violate the standard assumption that input is certain. Touch, speech recognition, gestural input, and sensors for context often produce uncertain estimates of user inputs. Current systems tend to remove uncertainty early on. However, information available in the user interface and application can help to resolve uncertainty more appropriately for the end user. This paper presents a set of techniques for tracking the state of interactive objects in the presence of uncertain inputs. These techniques use a Monte Carlo approach to maintain a probabilistically accurate description of the user interface that can be used to make informed choices about actions. Samples are used to approximate the distribution of possible inputs, possible interactor states that result from inputs, and possible actions (callbacks and feedback) interactors may execute. Because each sample is certain, the developer can specify most of the behavior of interactors in a familiar, non-probabilistic fashion. This approach retains all the advantages of maintaining information about uncertainty while minimizing the need for the developer to work in probabilistic terms. We present a working implementation of our framework and illustrate the power of these techniques within a paint program that includes three different kinds of uncertain input.

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

2010
 
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Schwarz, Julia, Harrison, Chris, Hudson, Scott E. and Mankoff, Jennifer (2010): Cord input: an intuitive, high-accuracy, multi-degree-of-freedom input method for mobile devices. In: Proceedings of ACM CHI 2010 Conference on Human Factors in Computing Systems 2010. pp. 1657-1660.

A cord, although simple in form, has many interesting physical affordances that make it powerful as an input device. Not only can a length of cord be grasped in different locations, but also pulled, twisted and bent -- four distinct and expressive dimensions that could potentially act in concert. Such an input mechanism could be readily integrated into headphones, backpacks, and clothing. Once grasped in the hand, a cord can be used in an eyes-free manner to control mobile devices, which often feature small screens and cramped buttons. In this note, we describe a proof-of-concept cord-based sensor, which senses three of the four input dimensions we propose. In addition to a discussion of potential uses, we also present results from our preliminary user study. The latter sought to compare the targeting performance and selection accuracy of different cord-based input modalities. We conclude with brief set of design recommendations drawn upon results from our study.

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

 
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Schwarz, Julia, Hudson, Scott E., Mankoff, Jennifer and Wilson, Andrew D. (2010): A framework for robust and flexible handling of inputs with uncertainty. In: Proceedings of the 2010 ACM Symposium on User Interface Software and Technology 2010. pp. 47-56.

New input technologies (such as touch), recognition based input (such as pen gestures) and next-generation interactions (such as inexact interaction) all hold the promise of more natural user interfaces. However, these techniques all create inputs with some uncertainty. Unfortunately, conventional infrastructure lacks a method for easily handling uncertainty, and as a result input produced by these technologies is often converted to conventional events as quickly as possible, leading to a stunted interactive experience. We present a framework for handling input with uncertainty in a systematic, extensible, and easy to manipulate fashion. To illustrate this framework, we present several traditional interactors which have been extended to provide feedback about uncertain inputs and to allow for the possibility that in the end that input will be judged wrong (or end up going to a different interactor). Our six demonstrations include tiny buttons that are manipulable using touch input, a text box that can handle multiple interpretations of spoken input, a scrollbar that can respond to inexactly placed input, and buttons which are easier to click for people with motor impairments. Our framework supports all of these interactions by carrying uncertainty forward all the way through selection of possible target interactors, interpretation by interactors, generation of (uncertain) candidate actions to take, and a mediation process that decides (in a lazy fashion) which actions should become final.

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

 
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Schwarz, Julia (2010): Towards a unified framework for modeling, dispatching, and interpreting uncertain input. In: Proceedings of the 2010 ACM Symposium on User Interface Software and Technology 2010. pp. 367-370.

Many new input technologies (such as touch and voice) hold the promise of more natural user interfaces. However, many of these technologies create inputs with some uncertainty. Unfortunately, conventional infrastructure lacks a method for easily handling uncertainty, and as a result input produced by these technologies is often converted to conventional events as quickly as possible, leading to a stunted interactive experience. Our ongoing work aims to design a unified framework for modeling uncertain input and dispatching it to interactors. This should allow developers to easily create interactors which can interpret uncertain input, give the user appropriate feedback, and accurately resolve any ambiguity. This abstract presents an overview of the design of a framework for handling input with uncertainty and describes topics we hope to pursue in future work. We also give an example of how we built highly accurate touch buttons using our framework. For examples of what interactors can be built and a more detailed description of our framework we refer the reader to [8].

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

2009
 
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Schwarz, Julia, Mankoff, Jennifer and Matthews, H. Scott (2009): Reflections of everyday activities in spending data. In: Proceedings of ACM CHI 2009 Conference on Human Factors in Computing Systems 2009. pp. 1737-1740.

In this paper we show that financial information can be used to sense many aspects of human activity. This simple technique gives people information about their daily lives, is easily accessible to many at no extra cost, requires little setup, and does not require the manufacture of any external devices. We will focus on how financial data can be used to show users where they spend their time, when they accomplish certain habits, and what the impact of their activities is on the environment. We validate our idea by implementing three demonstration applications intended for personal use. Finally, this paper discusses limitations of sensing using financial data and possible solutions.

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

 
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