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International audience ; In this paper we use entropy statistics to measure the synergies of knowledge exploration, knowledge exploitation, and organizational control in Hungary. We categorized the firms in terms of sub-regions, industrial sectors, and firm size. Configurational information among these distributions is the indicator of the synergy in the system. The results indicate that three regimes were generated in the Hungarian transition period with different dynamics: Budapest emerges as a knowledge-based innovation system; in the north-western regions, foreign-owned companies have induced a shift in knowledge-organization; while the system is organized in the southern-eastern regions in accordance with government expenditures.

In this paper we use entropy statistics to measure the synergies of knowledge exploration, knowledge exploitation, and organizational control in Hungary. We categorized the firms in terms of sub-regions, industrial sectors, and firm size. Configurational information among these distributions is the indicator of the synergy in the system. The results indicate that three regimes were generated in the Hungarian transition period with different dynamics: Budapest emerges as a knowledge-based innovation system; in the north-western regions, foreign-owned companies have induced a shift in knowledge-organization; while the system is organized in the southern-eastern regions in accordance with government expenditures.

AbstractViral marketing campaigns target primarily those individuals who are central in social networks and hence have social influence. Marketing events, however, may attract diverse audience. Despite the importance of event marketing, the influence of heterogeneous target groups is not well understood yet. In this paper, we define the Audience Selection (AS) problem in which different sets of agents need to be evaluated and compared based on their social influence. A typical application of Audience selection is choosing locations for a series of marketing events. The Audience selection problem is different from the well-known Influence Maximization (IM) problem in two aspects. Firstly, it deals with sets rather than nodes. Secondly, the sets are diverse, composed by a mixture of influential and ordinary agents. Thus, Audience selection needs to assess the contribution of ordinary agents too, while IM only aims to find top spreaders. We provide a systemic test for ranking influence measures in the Audience Selection problem based on node sampling and on a novel statistical method, the Sum of Ranking Differences. Using a Linear Threshold diffusion model on two online social networks, we evaluate eight network measures of social influence. We demonstrate that the statistical assessment of these influence measures is remarkably different in the Audience Selection problem, when low-ranked individuals are present, from the IM problem, when we focus on the algorithm's top choices exclusively.

Abstract
Core objectives of European common market integration are convergence and economic growth, but these are hampered by redundancy, and value chain asymmetries. The challenge is how to harmonize labor division to reach global competitiveness, meanwhile bridging productivity differences across the EU. We develop a bipartite network approach to trace pairwise co-specialization by applying the revealed comparative advantage method within and between the EU15 and Central and Eastern European (CEE). This approach assesses redundancies and the division of labor in the EU at the level of industries and countries. We find significant co-specialization among CEE countries but a diverging specialization between EU15 and CEE. Productivity increases in those CEE industries that have co-specialized with other CEE countries after EU accession, while co-specialization across CEE and EU15 countries is less related to productivity growth. These results show that a division of sectoral specialization can lead to productivity convergence between EU15 and CEE countries.