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- W1975680676 abstract "In a social network, users can sort members of their social graph into friend lists to both understand the social structures within the graph and control the flow of incoming and outgoing information. To reduce the user-effort required to create these lists, previous work has developed techniques for generating friend-lists in a static social graph. This paper considers the user effort required to create friend lists in an evolving graph. We have developed several new initial quantitative metrics to capture this effort, and identified an initial technique for modeling graph growth. We have used these metrics and model to compare two techniques for evolving friend lists when the social graph grows: manual evolution - the user evolves friend lists using no external tools -- and full recommendation -- an existing state of the art tool recommends a whole new set of friend lists. In these comparisons, we used the friend lists of 12 individuals, and simulated the growth of their social graphs and friend lists using our graph-growth model. Intuitively, when the graph evolves by a small (large) amount, the manual (automatic) approach should perform better. Our experiments show that full recommendation performs better than manual when the social graph changes by more than 1%, and yields an almost complete reduction in effort in the best cases." @default.
- W1975680676 created "2016-06-24" @default.
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- W1975680676 date "2013-10-12" @default.
- W1975680676 modified "2023-09-26" @default.
- W1975680676 title "Evolving friend lists in social networks" @default.
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- W1975680676 doi "https://doi.org/10.1145/2507157.2507194" @default.
- W1975680676 hasPublicationYear "2013" @default.
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