{"id":334781,"date":"2016-12-11T12:38:29","date_gmt":"2016-12-11T20:38:29","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=334781"},"modified":"2018-10-16T20:05:37","modified_gmt":"2018-10-17T03:05:37","slug":"distributed-sensemaking-improving-sensemaking-leveraging-efforts-previous-users","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/distributed-sensemaking-improving-sensemaking-leveraging-efforts-previous-users\/","title":{"rendered":"Distributed Sensemaking: Improving Sensemaking by Leveraging the Efforts of Previous Users"},"content":{"rendered":"

We examine the possibility of distributed sensemaking: improving a user\u2019s sensemaking by leveraging previous users\u2019 work without those users directly collaborating or even knowing one another. We asked users to engage in sensemaking by organizing and annotating web search results into \u201cknowledge maps,\u201d either with or without previous users\u2019 maps to work from. We also recorded gaze patterns as users examined others\u2019 knowledge maps. Our findings show the conditions under which distributed sensemaking can improve sensemaking quality; that a user\u2019s sensemaking process is readily apparent to a subsequent user via a knowledge map; and that the organization of content was more useful to subsequent users than the content itself, especially when those users had differing goals. We discuss the role distributed sensemaking can play in schema induction by helping users make a mental model of an information space and make recommendations for new tool and system development.<\/p>\n","protected":false},"excerpt":{"rendered":"

We examine the possibility of distributed sensemaking: improving a user\u2019s sensemaking by leveraging previous users\u2019 work without those users directly collaborating or even knowing one another. We asked users to engage in sensemaking by organizing and annotating web search results into \u201cknowledge maps,\u201d either with or without previous users\u2019 maps to work from. We also […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13559],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-334781","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-social-sciences","msr-locale-en_us"],"msr_publishername":"ACM","msr_edition":"CHI '12 Proceedings of the SIGCHI Conference on Human Factors in Computing 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