By Adam Wierzbicki, Ulrik Brandes, Frank Schweitzer, Dino Pedreschi
This publication constitutes the refereed court cases of the twelfth overseas 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 rigorously reviewed and chosen from fifty nine submissions. The papers take care of 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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Additional resources for Advances in Network Science: 12th International Conference and School, NetSci-X 2016, Wroclaw, Poland, January 11-13, 2016, Proceedings
However, averaging out the seasonal ﬂuctuation, customer sophistication captures the overall downward trend of GDP. The ﬁnancial crisis eﬀect was not only a macroeconomic problem, it also aﬀected the sophistication of the satisﬁable needs of the population. Note that, again, we have a negative correlation. This means that, as GDP shrinks, customers become more sophisticated. This is because the needs that once were classiﬁed as basic are not basic any more, hence the rise in sophistication of the population.
In this work, we borrow these indicators and we use them to tackle the problem of nowcasting GDP. An alternative methodology uses electronic payment data . However in this case the only issue addressed is the timing issue, but no attempt is made into making the measure more representative of the satisfaction of people’s needs. The critiques to GDP we mentioned have resulted in the proliferation of alternative well-being indicators. We mention the Index of Sustainable Economic Welfare (ISEW), the Genuine Progress Indicator (GPI)  and the Human Development Index (HDI)1 .
More research is needed to fully understand this dynamic. Going Beyond GDP to Nowcast Well-Being Using Retail Market Data 41 Finally, in this paper we made use of a quarterly aggregation to build our bipartite networks. We made this choice because the quarterly aggregation is the most ﬁne-grained one we can obtain for GDP estimations. However, now that we showed the correlation, we might investigate if the quarterly aggregation is the most appropriate for our analysis. If we can obtain comparable results with a lower level of aggregation (say monthly or weekly) our well-being estimation can come closer to be calculated almost in real-time.
Advances in Network Science: 12th International Conference and School, NetSci-X 2016, Wroclaw, Poland, January 11-13, 2016, Proceedings by Adam Wierzbicki, Ulrik Brandes, Frank Schweitzer, Dino Pedreschi