<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xiaomu Zhou</style></author><author><style face="normal" font="default" size="100%">Mark S. Ackerman</style></author><author><style face="normal" font="default" size="100%">Kai Zheng</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The Recording and Reuse of Psychosocial Information in Care</style></title><secondary-title><style face="normal" font="default" size="100%">Designing Healthcare That Works:  A Socio-technical Approach</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year></dates><publisher><style face="normal" font="default" size="100%">Academic Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Cambridge, MA</style></pub-location><pages><style face="normal" font="default" size="100%">133-148</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xiaomu Zhou</style></author><author><style face="normal" font="default" size="100%">Kai Zheng</style></author><author><style face="normal" font="default" size="100%">Mark S. Ackerman</style></author><author><style face="normal" font="default" size="100%">David A Hanauer</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Cooperative documentation: the patient problem list as a nexus in electronic health records</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the ACM 2012 Conference on Computer Supported Cooperative Work (CSCW ’12)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">health information</style></keyword><keyword><style  face="normal" font="default" size="100%">information access</style></keyword><keyword><style  face="normal" font="default" size="100%">medical informatics</style></keyword><keyword><style  face="normal" font="default" size="100%">medical information</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">01/02/2012</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">Complete</style></url></web-urls></urls><pages><style face="normal" font="default" size="100%">853-862</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The patient Problem List (PL) is a mandated documentation component of electronic health records supporting the longitudinal summarization of patient information in addition to facilitating the coordination of care by multidisciplinary medical teams. In this paper, we report an ethnographic study that examined the institutionalization of the PL. Specifically, we explored: (1) how different groups (primary care providers, inpatient hospitalists, specialists, and emergency doctors) perceived the purposes of the PL differently; (2) how these deviated perceptions might affect their use of the PL; and (3) how the technical design of the PL facilitated or hindered the clinical practices of these groups. We found significant ambiguity regarding the definition, benefits, and use of the PL across different groups. We also found that certain groups (e.g. primary care providers) had developed effective cooperative strategies regarding the use of the PL; however, suboptimal usage was common among other user types, which could have a profound impact on quality of care and safety. Based on these findings, we provide suggestions to improve the design of the PL, particularly on strengthening its support on longitudinal and cooperative clinical practices.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sacha Zyto</style></author><author><style face="normal" font="default" size="100%">David R. Karger</style></author><author><style face="normal" font="default" size="100%">Mark S. Ackerman</style></author><author><style face="normal" font="default" size="100%">Mahajan, Sanjoy</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Successful Classroom Deployment of a Social Document Annotation System</style></title><secondary-title><style face="normal" font="default" size="100%">ACM Conference on Human Factors in Computing Systems (CHI’12), May, 2012</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">annotation</style></keyword><keyword><style  face="normal" font="default" size="100%">collaboration</style></keyword><keyword><style  face="normal" font="default" size="100%">e-learning</style></keyword><keyword><style  face="normal" font="default" size="100%">forum</style></keyword><keyword><style  face="normal" font="default" size="100%">hypertext</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2012</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">Complete-OnlyDOI</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;NB is an in-place collaborative document annotation website targeting students reading lecture notes and draft textbooks. Serving as a discussion forum in the document margins, NB lets users ask and answer questions about their reading material &lt;em&gt;as they are reading&lt;/em&gt;. NB users can read and annotate documents using their web browsers, without any special plug-ins. We describe the NB system and its evaluation in real class environment, where students used it to submit their reading assignments, ask questions and get or provide feedback. We show that this tool can be and has been successfully incorporated into a number of different classes at different institutions. To understand how and why, we focus on a particularly successful class deployment where the instructor adapted his teaching style to take students&#039; comment into account. We analyze the annotation practices that were observed - including the way geographic locality was exploited in ways unavailable in traditional forums - and discuss general design implications for online annotation tools in academia.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xiaomu Zhou</style></author><author><style face="normal" font="default" size="100%">Mark S. Ackerman</style></author><author><style face="normal" font="default" size="100%">Kai Zheng</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">CPOE workarounds, boundary objects, and assemblages</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI’11)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">assemblage</style></keyword><keyword><style  face="normal" font="default" size="100%">boundary object</style></keyword><keyword><style  face="normal" font="default" size="100%">CPOE</style></keyword><keyword><style  face="normal" font="default" size="100%">cscw</style></keyword><keyword><style  face="normal" font="default" size="100%">EHR</style></keyword><keyword><style  face="normal" font="default" size="100%">electronic patient records</style></keyword><keyword><style  face="normal" font="default" size="100%">health informatics</style></keyword><keyword><style  face="normal" font="default" size="100%">health information</style></keyword><keyword><style  face="normal" font="default" size="100%">information access</style></keyword><keyword><style  face="normal" font="default" size="100%">medical informatics</style></keyword><keyword><style  face="normal" font="default" size="100%">medical information</style></keyword><keyword><style  face="normal" font="default" size="100%">medical orders</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">5/2010</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">Complete</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We conducted an ethnographically based study at a large teaching hospital to examine clinician workarounds engendered by the adoption of a Computerized Prescribe Order Entry (CPOE) system. Specifically, we investigated how adoption of computerized systems may alter medical practice, order management in particular, as manifested through the working-around behavior developed by doctors and nurses to accommodate the changes in their day-to-day work environment. In this paper, we focus on clinicians’ workarounds, including those workarounds that gradually disappeared and those that have become routinized. Further, we extend the CSCW concept of boundary object (to &quot;assemblage&quot;) in order to understand the workarounds created with CPOE system use and the changing nature of clinical practices that are increasingly computerized.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xiaomu Zhou</style></author><author><style face="normal" font="default" size="100%">Mark S. Ackerman</style></author><author><style face="normal" font="default" size="100%">Kai Zheng</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Computerization and information assembling process: nursing work and CPOE adoption</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 1st ACM International Health Informatics Symposium (IHI ’10)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">CPOE</style></keyword><keyword><style  face="normal" font="default" size="100%">electronic medical records</style></keyword><keyword><style  face="normal" font="default" size="100%">health informatics</style></keyword><keyword><style  face="normal" font="default" size="100%">information access</style></keyword><keyword><style  face="normal" font="default" size="100%">information assembling</style></keyword><keyword><style  face="normal" font="default" size="100%">information system</style></keyword><keyword><style  face="normal" font="default" size="100%">medical informatics</style></keyword><keyword><style  face="normal" font="default" size="100%">personal sheet</style></keyword><keyword><style  face="normal" font="default" size="100%">shift change</style></keyword><keyword><style  face="normal" font="default" size="100%">working document</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2010</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">Complete</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This paper presents an ethnographic study investigating how nurses assemble information to start their shift’s work. We examined this process before and after the adoption of a Computerized Prescriber Order Entry (CPOE) system in an inpatient unit of a large teaching hospital. Before the CPOE adoption, nurses used several collaboratively-created group working documents to assist in this information assembling process; after the CPOE adoption, they mainly used the CPOE itself for their information needs. We found while computerization facilitated medical data assembling process and improved order handling practice, it also resulted in some information gaps in understanding patients in their larger care context. We analyzed what it means when the computerization of medical information turns local knowledge into more readily available and public information objects, as well as what that means for patients and patient care.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xiaomu Zhou</style></author><author><style face="normal" font="default" size="100%">Mark S. Ackerman</style></author><author><style face="normal" font="default" size="100%">Kai Zheng</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Doctors and Psychosocial Information: Records and Reuse in Inpatient Care</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI’10)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">EHR</style></keyword><keyword><style  face="normal" font="default" size="100%">electronic patient records</style></keyword><keyword><style  face="normal" font="default" size="100%">health informaticshealth informatics</style></keyword><keyword><style  face="normal" font="default" size="100%">information access</style></keyword><keyword><style  face="normal" font="default" size="100%">information reuse</style></keyword><keyword><style  face="normal" font="default" size="100%">medical information</style></keyword><keyword><style  face="normal" font="default" size="100%">medical records</style></keyword><keyword><style  face="normal" font="default" size="100%">organizational memory</style></keyword><keyword><style  face="normal" font="default" size="100%">physician information needs</style></keyword><keyword><style  face="normal" font="default" size="100%">psychosocial information</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">Complete</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We conducted a field-based study at a large teaching hospital to examine doctors’ use and documentation of patient care information, with a special focus on a patient’s psychosocial information. We were particularly interested in the gaps between the medical work and any representations of the patient. The paper describes how doctors record this information for immediate and long-term use. We found that doctors documented a considerable amount of psychosocial information in their electronic health records (EHR) system. Yet, we also observed that such information was recorded selectively, and a medicalized view-point is a key contributing factor. Our study shows how missing or problematic representations of a patient affect work activities and patient care. We accordingly suggest that EHR systems could be made more usable and useful in the long run, by supporting both representations of medical processes and of patients.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xiaomu Zhou</style></author><author><style face="normal" font="default" size="100%">Mark S. Ackerman</style></author><author><style face="normal" font="default" size="100%">Kai Zheng</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">I just don&#039;t know why it&#039;s gone: Maintaining Informal Information Use in Inpatient Care</style></title><secondary-title><style face="normal" font="default" size="100%">ACM Conference on Human Factors in Computing Systems (CHI&#039;09)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">CPOE</style></keyword><keyword><style  face="normal" font="default" size="100%">electronic patient records</style></keyword><keyword><style  face="normal" font="default" size="100%">informal information</style></keyword><keyword><style  face="normal" font="default" size="100%">medical informatics.</style></keyword><keyword><style  face="normal" font="default" size="100%">medical records</style></keyword><keyword><style  face="normal" font="default" size="100%">organizational memory</style></keyword><keyword><style  face="normal" font="default" size="100%">psychosocial information</style></keyword><keyword><style  face="normal" font="default" size="100%">shift change</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">04/2009</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">Complete</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We conducted a field-based study examining informal nursing information. We examined the use of this information before and after the adoption of a CPOE (Computerized Provider Order Entry) system in an inpatient unit of a large teaching hospital. Before CPOE adoption,&lt;br&gt;nurses used paper working documents to detail psychosocial information about patients; after the CPOE adoption, they did not use paper or digital notes as was planned. The paper describes this process and analyses how several interlocked reasons contributed to the loss of this information in written form. We found that a change in physical location, sufficient convenience, visibility of the information, and permanency of information account for some, but not all, of the outcome. As well, we found that computerization of the nursing data led to a shift in the politics of the information itself – the nurses no longer had a cohesive agreement about the kinds of data to enter into the system. The findings address the requirements of healthcare computerization to support both formal and informal work practices, respecting the nature of nursing work and the politics of information inherent in complex medical work.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lada A. Adamic</style></author><author><style face="normal" font="default" size="100%">Zhang, Jun</style></author><author><style face="normal" font="default" size="100%">Bakshy, Eytan</style></author><author><style face="normal" font="default" size="100%">Mark S. Ackerman</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Knowledge Sharing and Yahoo Answers: Everyone Knows Something</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 17th International Conference on World Wide Web</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">expertise finding</style></keyword><keyword><style  face="normal" font="default" size="100%">expertise sharing</style></keyword><keyword><style  face="normal" font="default" size="100%">help seeking</style></keyword><keyword><style  face="normal" font="default" size="100%">knowledge sharing</style></keyword><keyword><style  face="normal" font="default" size="100%">online communities</style></keyword><keyword><style  face="normal" font="default" size="100%">Q&amp;A communities</style></keyword><keyword><style  face="normal" font="default" size="100%">QA communities</style></keyword><keyword><style  face="normal" font="default" size="100%">question answering</style></keyword><keyword><style  face="normal" font="default" size="100%">social network analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">Complete</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Yahoo Answers (YA) is a large and diverse question-answer forum, acting not only as a medium for sharing technical knowledge, but as a place where one can seek advice, gather opinions, and satisfy one&#039;s curiosity about a countless number of things. In this paper, we seek to understand YA&#039;s knowledge sharing and activity. We analyze the forum categories and cluster them according to content characteristics and patterns of interaction among the users. While interactions in some categories resemble expertise sharing forums, others incorporate discussion, everyday advice, and support. With such a diversity of categories in which one can participate, we find that some users focus narrowly on specific topics, while others participate across categories. This not only allows us to map related categories, but to characterize the entropy of the users&#039; interests. We find that lower entropy correlates with receiving higher answer ratings, but only for categories where factual expertise is primarily sought after. We combine both user attributes and answer characteristics to predict, within a given category, whether a particular answer will be chosen as the best answer by the asker.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mark S. Ackerman</style></author><author><style face="normal" font="default" size="100%">Hofer, Erik C</style></author><author><style face="normal" font="default" size="100%">Hanisch, Robert J</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Olson, Gary M</style></author><author><style face="normal" font="default" size="100%">Zimmerman, Ann</style></author><author><style face="normal" font="default" size="100%">Bos, Nathan</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">The national virtual observatory</style></title><secondary-title><style face="normal" font="default" size="100%">Scientific collaboration on the Internet</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">astronomy</style></keyword><keyword><style  face="normal" font="default" size="100%">big data</style></keyword><keyword><style  face="normal" font="default" size="100%">cyberinfrastructure</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><publisher><style face="normal" font="default" size="100%">MIT Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Cambridge, MA</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Like many scientific communities, the astronomy community faces a coming avalanche of data as instrumentation improves in quality as well as in its ability to integrate with computational and data resources. Unlike scientific fields that are oriented around a small number of major instruments, such as high-energy physics, astronomers use a large number of telescopes located around the world that are designed and calibrated to look at celestial objects in fundamentally different ways. Both space and terrestrial telescopes are designed to observe objects across a narrow part of the energy spectrum, typically focusing on a small part of the spectrum from the infrared to X-ray wavelengths. While each telescope has the potential to reveal and characterize new astronomical objects, even more powerful would be the ability to combine the data produced by each of these instruments to create a unified picture of the observable universe. This data fusion requires federating a large number of data sets, and developing the search and analysis routines that allow investigation across multiple wavelengths.&lt;/p&gt;&lt;p&gt;The National Virtual Observatory (NVO) project is funded by the National Science Foundation (NSF) to provide the cyberinfrastructure necessary to support the federation of a large number of astronomical data sets, allowing search across multiple data sets and the development of simulations that incorporate many types of astronomical data. Through the development of tools and standardized data models, the NVO hopes to enable the combination of multiple pointed-observation telescopes and sky surveys into a large, unified data set that effectively functions as a broadband, worldwide telescope. The NVO is part of a larger effort, known as the International Virtual Observatory Alliance (IVOA), to support data federation and exchange across a number of national and regional virtual observatories.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhang, Jun</style></author><author><style face="normal" font="default" size="100%">Mark S. Ackerman</style></author><author><style face="normal" font="default" size="100%">Lada A. Adamic</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">CommunityNetSimulator: Using simulations to study online community networks</style></title><secondary-title><style face="normal" font="default" size="100%">Communities and Technologies 2007</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">community dynamics</style></keyword><keyword><style  face="normal" font="default" size="100%">community strucure</style></keyword><keyword><style  face="normal" font="default" size="100%">incentive structures</style></keyword><keyword><style  face="normal" font="default" size="100%">online communities</style></keyword><keyword><style  face="normal" font="default" size="100%">Q&amp;A communities</style></keyword><keyword><style  face="normal" font="default" size="100%">QA communities</style></keyword><keyword><style  face="normal" font="default" size="100%">reward structures</style></keyword><keyword><style  face="normal" font="default" size="100%">simulation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">Complete</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pages><style face="normal" font="default" size="100%">295–321</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Help-seeking communities have been playing an increasingly critical role the way people seek and share information online, forming the basis for knowledge dissemination and accumulation. Consider:&lt;/p&gt;&lt;p&gt;❑ About.com, a popular help site (http://about.com), boasts 30 million distinct users each month&lt;/p&gt;&lt;p&gt;❑ Knowledge-iN, a Korean site (http://kin.naver.com/), has accumulated 1.5 million question and answers.&lt;/p&gt;&lt;p&gt;Many additional sites exist from online stock trading discussions to medicaladvice communities. These range from simple text-based newsgroups to intricate immersive virtual reality multi-user worlds. Unfortunately, the very size of these communities may impede an individual’s ability to find relevant answers or advice. Which replies were written by experts and which by novices? As these help-seeking communities are also often primitive technically, they often cannot help the user distinguish between e.g. expert and novice advice. We would therefore like to find mechanisms to augment their functionality and social life. Research is proceeding to make use of the available structure in online communities to design new systems and &amp;nbsp;algorithms (e.g., [4], [10]). These are largely focused on social network characteristics of these communities.&lt;/p&gt;&lt;p&gt;However, differing network structures and dynamics will affect possible algorithms that attempt to make use of these networks, but little is known of these impacts.&lt;/p&gt;&lt;p&gt;Accordingly, we developed a CommunityNetSimulator (CNS), a simulator that combines various network models, as well as various new social network analysis techniques that are useful to study online community (or virtual organization) network formation and dynamics.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhang, Jun</style></author><author><style face="normal" font="default" size="100%">Mark S. Ackerman</style></author><author><style face="normal" font="default" size="100%">Lada A. Adamic</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Expertise networks in online communities: structure and algorithms</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 16th international conference on World Wide Web (WWW&#039;07)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">expert locators</style></keyword><keyword><style  face="normal" font="default" size="100%">expertise finding</style></keyword><keyword><style  face="normal" font="default" size="100%">help seeking</style></keyword><keyword><style  face="normal" font="default" size="100%">online communities</style></keyword><keyword><style  face="normal" font="default" size="100%">simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">social network analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2007</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">Complete</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">ACM</style></publisher><pages><style face="normal" font="default" size="100%">221–230</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Web-based communities have become important places for people to seek and share expertise. We find that networks in these communities typically differ in their topology from other online networks such as the World Wide Web. Systems targeted to augment web-based communities by automatically identifying users with expertise, for example, need to adapt to the underlying interaction dynamics. In this study, we analyze the Java Forum, a large online help-seeking community, using social network analysis methods. We test a set of network-based ranking algorithms, including PageRank and HITS, on this large size social network in order to identify users with high expertise. We then use simulations to identify a small number of simple simulation rules governing the question-answer dynamic in the network. These simple rules not only replicate the structural characteristics and algorithm performance on the empirically observed Java Forum, but also allow us to evaluate how other algorithms may perform in communities with different characteristics. We believe this approach will be fruitful for practical algorithm design and implementation for online expertise-sharing communities.&lt;br&gt;&amp;nbsp;&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhang, Jun</style></author><author><style face="normal" font="default" size="100%">Mark S. Ackerman</style></author><author><style face="normal" font="default" size="100%">Lada A. Adamic</style></author><author><style face="normal" font="default" size="100%">Kevin K. Nam</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">QuME: A Mechanism to Support Expertise Finding in Online Help-seeking Communities</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 20th Annual ACM Symposium on User Interface Software and Technology (UIST&#039;07)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">cscw</style></keyword><keyword><style  face="normal" font="default" size="100%">expertise finding</style></keyword><keyword><style  face="normal" font="default" size="100%">expertise location</style></keyword><keyword><style  face="normal" font="default" size="100%">social networks</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2007</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">Complete</style></url></web-urls></urls><pages><style face="normal" font="default" size="100%">111–114</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Help-seeking communities have been playing an increasingly critical role in the way people seek and share information. However, traditional help-seeking mechanisms of these online communities have some limitations. In this paper, we describe an expertise-finding mechanism that attempts to alleviate the limitations caused by not knowing users&#039; expertise levels. As a result of using social network data from the online community, this mechanism can automatically infer expertise level. This allows, for example, a question list to be personalized to the user&#039;s expertise level as well as to keyword similarity. We believe this expertise location mechanism will facilitate the development of next generation help-seeking communities.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Wayne G Lutters</style></author><author><style face="normal" font="default" size="100%">Mark S. Ackerman</style></author><author><style face="normal" font="default" size="100%">Xiaomu Zhou</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Jones, William P.</style></author><author><style face="normal" font="default" size="100%">Jaime Teevan</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Group information management</style></title><secondary-title><style face="normal" font="default" size="100%">Personal Information Management</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">group information</style></keyword><keyword><style  face="normal" font="default" size="100%">personal information management</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">Complete</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">University of Washington Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Seattle, WA</style></pub-location><pages><style face="normal" font="default" size="100%">236–248</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&amp;nbsp;&lt;/p&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;&lt;p&gt;Activities of PIM are often embedded in group or organizational contexts. To work effectively within a group, an individual must manage information not only for his or her personal use but also to share with other members of the group. Obviously, one would like to leverage the activities of others around. Being able to obtain telephone numbers, schedule group meetings, determine the availability of one’s peers, and obtain important collaborative information is invaluable. What are the issues, if any, in leveraging the work of others, in order to incorporate their calendar, contacts, and other information into one’s own PIM system? And what would be involved in sharing one’s own data for use by others?&amp;nbsp;&lt;/p&gt;&lt;p&gt;This chapter reviews the host of issues involved in the collaborative use of personal information. Topics covered include motivation, adoption patterns, interaction styles, control over personal information, privacy, and trust. The goal is to facilitate sharing personal information by considering these issues; fully considered, they can enable the cooperative adoption and use of tools to support group information management (GIM).&amp;nbsp;&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhang, Jun</style></author><author><style face="normal" font="default" size="100%">Mark S. Ackerman</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Searching for Expertise in Social Networks: A Simulation of Potential Strategies</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 2005 International ACM SIGGROUP Conference on Supporting Group Work (Group&#039;05)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">expertise finding</style></keyword><keyword><style  face="normal" font="default" size="100%">expertise location</style></keyword><keyword><style  face="normal" font="default" size="100%">expertise sharing</style></keyword><keyword><style  face="normal" font="default" size="100%">information seeking</style></keyword><keyword><style  face="normal" font="default" size="100%">organizational simulations</style></keyword><keyword><style  face="normal" font="default" size="100%">social computing</style></keyword><keyword><style  face="normal" font="default" size="100%">social networks</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">Complete</style></url></web-urls></urls><pages><style face="normal" font="default" size="100%">71–80</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;People search for people with suitable expertise all of the time in their social networks - to answer questions or provide help. Recently, efforts have been made to augment this searching. However, relatively little is known about the social characteristics of various algorithms that might be useful. In this paper, we examine three families of searching strategies that we believe may be useful in expertise location. We do so through a simulation, based on the Enron email data set. (We would be unable to suitably experiment in a real organization, thus our need for a simulation.) Our emphasis is not on graph theoretical concerns, but on the social characteristics involved. The goal is to understand the tradeoffs involved in the design of social network based searching engines.&lt;br&gt;&amp;nbsp;&lt;/p&gt;</style></abstract></record></records></xml>