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Temporal Distance Metrics for Social Network Analysis

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The analysis of social and technological networks has attracted a lot of attention as social networking applications and mobile sensing devices have given us a wealth of real data. Classic studies looked at analysing static networks, i.e., networks that do not change over time or built as the results of aggregation of information over a certain period of time, however researchers are quickly starting to realise that connections inherently vary over time and exhibit more dimensionality than static analysis can capture. This talklet presents work on temporal graphs and a set of temporal metrics that capture the information diffusion properties of a social network.

This talk is part of the Computer Laboratory NetOS Group Talklets series.

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