Network Analysis LiteracyNetwork analysis literacy is concerned with when to use which method to analyze networks. The field has seen many methods being proposed in these areas - but as we show in the article, not many of them have been evaluated with respect to some ground truth. We propose that the network analysis community should agree on benchmark data sets and ground truth or gold standard solutions to show that the proposed algorithms can be tested with regard to their quality.
Publications in this project: A first project in that direction was conducted together with Sudarsan Iyengar and his colleagues on human navigation in complex networks. In this cooperation we worked on analyzing how people learn to navigage in a highly abstract, word-based network.
One plus one makes three for social networksIn this cooperation with Michael Hanselmann and Fred Hamprecht we explored how much a typcial social network platform (like Facebook) can infer about relationships between non-members. Based on the information of who knows whom on the platfrom and a list of contacts to non-members we estimate that a platform like facebook can infer about 40% of the connections between non-members. The
The paper was among the top-ten downloads for several weeks after publication and featured with a 'news and views' article.
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