Vizster: Visualizing Online Social Networks
INFOVIS '05 Proceedings of the Proceedings of the 2005 IEEE Symposium on Information Visualization
CrystalChat: Visualizing Personal Chat History
HICSS '06 Proceedings of the 39th Annual Hawaii International Conference on System Sciences - Volume 03
The project fragmentation problem in personal information management
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A personal approach: the persona technique in a companion's design lifecycle
INTERACT'11 Proceedings of the 13th IFIP TC 13 international conference on Human-computer interaction - Volume Part III
"Ten things i want to know about you": unveiling friends' attribute relevance
Proceedings of the 30th European Conference on Cognitive Ergonomics
Proceedings of the 24th ACM Conference on Hypertext and Social Media
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Our Personal Information is now scattered among several applications and personal devices in an unrelated, but still connected, information network. We have never had so much information at our disposal as we have now, giving us the opportunities to find information about other people, a very frequent need. While previous works have proposed several solutions to relate data from multiple sources that does not happen at the presentation level. When needing information about people, we still have to navigate among sources to find it. Besides troublesome, it is difficult to have an overall characterization of what each person represents to us. We argue that gathering information from all these sources and presenting it in a unified interface benefits the user by providing a quick and meaningful overview of who that person is and how he/she is related to him/her. We present Visualiz'em, a personal visualization tool based on three interconnected views: Profile, Tagcloud and Timeline. When compared to traditional applications Visualiz'em provides a faster and richer overview of whom a person is and his/her relationship with the user. Moreover, results show that our visualization tool promotes serendipitous behaviors, allowing users to easily explore data and find interaction patterns.