Advances in Network Science: 12th International Conference by Adam Wierzbicki, Ulrik Brandes, Frank Schweitzer, Dino

By Adam Wierzbicki, Ulrik Brandes, Frank Schweitzer, Dino Pedreschi

This ebook constitutes the refereed lawsuits of the twelfth foreign convention and faculty of community technology, NetSci-X 2016, held in Wroclaw, Poland, in January 2016.

The 12 complete and six brief papers have been conscientiously reviewed and chosen from fifty nine submissions. The papers care for the learn of community versions in domain names starting from biology and physics to desktop technology, from monetary markets to cultural integration, and from social media to infectious diseases.

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It is more in line with a real well-being measure, because it detaches itself from the mere quantity of money circulating in the country and focuses closely on the real dynamics of the population’s everyday life. The analysis we present is based on a dataset coming from a large retail company in Italy. The company operates ∼ 120 shops in the West Coast in Italy. It serves millions of customers every year, of which a large majority is identifiable through fidelity cards. We analyze all items sold from January 2007 to June 2014.

We set n = 5 and the ground truth topics are the “Like” topics. Other settings have consistent findings. We first observe that all our methods perform much better than Random for both lurker and active user 26 W. Gong et al. Table 3. Performance (MAP@n) of reading topic discovery. 2 Lurkers Active Users Fig. 5. Performance of predicting lurkers and active users’ reading topics. groups. Secondly, overall, predicting active users’ reading topics is easier than predicting lurkers’. Thirdly, Read-Popularity does not perform well for lurkers.

We therefore have two ranking strategies based on posted content and received content to predict user posting and reading topics respectively. They are Posted-Content and ReceivedContent strategies respectively. User posted and received content is commonly used for topic discovery [23,26,27]. The intuition of the Content strategies is that users are likely to be interested in the topics that their posted and received content is associated with. 22 W. Gong et al. The Content strategies rank topics as follows.

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