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A visual calendar for scheduling group meetings
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CSCW '92 Proceedings of the 1992 ACM conference on Computer-supported cooperative work
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CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Proceedings of the SIGCHI conference on Human Factors in Computing Systems
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Calendars on the new frontier: challenges of groupware technology
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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CSCW '02 Proceedings of the 2002 ACM conference on Computer supported cooperative work
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ACM Transactions on Computer-Human Interaction (TOCHI)
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Proceedings of the 3rd international conference on Mobile multimedia communications
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Proceedings of the 2008 ACM conference on Recommender systems
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Proceedings of the 2008 ACM conference on Computer supported cooperative work
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services
A personal meeting scheduling agent
Personal and Ubiquitous Computing
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Existing enterprise calendaring systems have suffered from problems like rigidity, lack of transparency, and poor integration with social networks. We present the system design and rationale for a novel social coordination mechanism, called "Suggestions," that addresses these issues. Our system integrates ideas drawn from designs of lightweight polling systems and one's social network into an open calendar tool, providing a space for users to coordinate, socialize around, or negotiate the "what" and the "when" of their events. Suggestions was released inside a large enterprise setting, where initial interviews revealed users' thoughts on transparent scheduling, reaching wider audiences and task appropriateness, and suggested ways to improve our design.