Practical RDF
A familiar face(book): profile elements as signals in an online social network
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Internet social network communities: Risk taking, trust, and privacy concerns
Computers in Human Behavior
An investigation into facebook friend grouping
INTERACT'11 Proceedings of the 13th IFIP TC 13 international conference on Human-computer interaction - Volume Part III
Finding someone in my social directory whom i do not fully remember or barely know
Proceedings of the 2012 ACM international conference on Intelligent User Interfaces
Visualiz'em: "show me more about him!"
Proceedings of the International Working Conference on Advanced Visual Interfaces
Proceedings of the 24th ACM Conference on Hypertext and Social Media
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Motivation -- The growing amount of personal information on the web raises increasing concerns about what and with whom we share information online. Nevertheless, little effort has been made in determining the relevance of the information shared with us or in filtering it accordingly. This is even more important considering our need to be constantly aware of what is happening in our friends' lives. Research approach -- A study to identify the most relevant characteristics when seeking information about friends and to scrutinize which specific features they mention. To achieve that, we resorted to interviews and questionnaires. We asked participants to describe people and asked them to rate the perceived relevance of a carefully pre-determined set of attributes. Findings/Design -- Results suggested that the most relevant attributes when seeking information about friends are: Personality, Relationship, Interests & Hobbies, Academic History, Profession, Phone, Email and Address. We also provide indications of the specific features people mention when referring these attributes. Take away message -- The relevance among attributes varies when seeking information about friends. It should be considered to warn users or highlight the changes when they occur in the most important attributes.