SÁNDOR JUHÁSZ, GERGŐ TÓTH, BALÁZS LENGYEL (HAS CERS): Brokering the Core with Periphery – Collaboration Networks and Individual Success in the Hungarian Film Industry
In collaboration-based creative industries, such as film production, connections to central creators can facilitate individual success; while brokering loosely connected communities provide additional advantages. However, there is still limited evidence on how brokerage in core/periphery networks influence nodal outcomes. In this paper, we argue that links to peripheral creators provide additional and complementary benefits for core members, such as access to novel creative ideas or free capacities. Consequently, those creators who broker the core with the periphery of the network enjoy both type of benefits and thus are more likely to achieve success. To verify the argument, we construct a dynamic network of movie creators based on a unique dataset of Hungarian feature films for the 1990-2009 period. We provide evidence that being in the core and brokering the network at the same time induce individual success together. Then, we construct a new way to capture brokers’ role in core/periphery networks and find that those creators who bridge the core with the periphery have an increased likelihood of award winning.
MICHAEL T. GASTNER (Yale-NUS College): Consensus time in a voter model with concealed and publicly expressed opinions
The voter model is a simple agent-based model to mimic opinion dynamics in social networks: a randomly chosen agent adopts the opinion of a randomly chosen neighbour. This process is repeated until a consensus emerges. Although the basic voter model is theoretically intriguing, it misses an important feature of real opinion dynamics: it does not distinguish between an agent's publicly expressed opinion and her inner conviction. A person may not feel comfortable declaring her conviction if her social circle appears to hold an opposing view. Here we introduce the Concealed Voter Model where we add a second, concealed layer of opinions to the public layer. If an agent's public and concealed opinions disagree, she can reconcile them by either publicly disclosing her previously secret point of view or by accepting her public opinion as inner conviction. We study a complete graph of agents who can choose from two opinions. We define a martingale M that determines the probability of all agents eventually agreeing on a particular opinion. By analyzing the evolution of M in the limit of a large number of agents, we derive the leading-order terms for the mean and standard deviation of the consensus time (i.e. the time needed until all opinions are identical). We thereby give a precise prediction by how much concealed opinions slow down a consensus.
MARTIN HALLA (University of Linz): The Effect of Superstition on Health Outcomes: Evidence from the Taiwanese Ghost Month
GERGŐ HAVADI, ORSOLYA RING, ATTILA GULYÁS, LÁSZLÓ KISS (HAS CSS RECENS): A Rákosi-rendszer hatalmi hálózatai – módszertani megfontolások és az első eredmények - Hungarian language lecture
Az 1949 és 1956 közti időszakban a hatalmi elit csoportja – élén Rákosi Mátyással – számos belső harc színtere volt. Célunk, hogy mindezeket az eleddig ismeretlen, rejtett folyamatokat, valamint az esetleges háttéralkukat feltárjuk. Kutatásunk alapjául az MDP különböző ülésein rögzített jegyzőkönyvek szolgálnak, melyek alapján felrajzoljuk a résztvevők kapcsolathálóját, majd mindezek alapján megállapításokat tegyünk a párthierarchia mögött húzódó látens kapcsolati struktúrákra.
DENIS HELIC (TU Graz): Tend to the User Core, Don't Neglect the Casuals: A Recipe for Growth of Q&A Web Communities
Millions of users on the Internet discuss a variety of topics on Question-and-Answer (Q&A) instances. However, not all instances and topics receive the same amount of attention, as some thrive and achieve self-sustaining levels of activity while others fail to attract users.It is imperative to not only better understand but also to distill
deciding factors and rules that define and govern sustainable Q&A instances. To that end, we extract, model and cluster user activity-based time series from selected Q&A instances from the Stack Exchange network to characterize user behavior. We find distinct types of user activity temporal patterns, which vary primarily according to the users' activity frequency. Moreover, we distill temporal dynamics of community activity and thereby identify key factors leading to success or failure of communities. Further, we compare groups of StackExchange communities of different topical focuses, such as STEM and humanities. We find that growing communities exhibit both a small core of power
users reacting to the community as a whole, and many casual users strongly interacting with other casual users, suggesting community openness towards less active users. Further, we find that communities in the humanities are centered around power users, whereas in STEM communities activity is more evenly distributed. With our analysis,we
provide insights for practitioners to quantitatively assess evolution and the activity potential of Q&A communities.