Back3 September, 2013
Brys Zoltán (Literatura Medica Network Science Section): Network Analysis of Pharmaceutical Ads in the Hungarian Medical Journals – Marketing versus Medicine
Co- authors: Horváth Gabriella, Buda Béla, Tímár György; Pluhár András
Promotion of medical products in medical journals is influenced by economic and professional (medicine) factors. Besides incentives, such ads still play a key role in influencing physician prescription behavior, which is a primer goal of Big Pharma marketing. Using graph-theory based network analysis we examined pharmaceutical ads in Hungarian medical journals. The dataset contained cumulated data of 39 months: 4413 promotional relationship between medicamentums (n=1642) and medical journals (m=99). Various distributions of the dataset showed power law distribution. Journal-Medicamentum bipartite graph were derived and converted into non-bipartite graphs (Journal-Journal and Medicamentum-Medicamentum.). Using the Anatomical Therapeutic Chemical Classification System and cluster analysis (Raghavan et al, 2007) we found that similar ATC coded drugs and similar professional journals tend to connect and form clusters. A real-life validated result of network analysis suggests further research in the field.
10 September, 2013
Michelle O. Crosby-Nagy (Corvinus University of Budapest): LinkedIn Ego Networks as a New Data Source for Innovation Network Studies?
Scientometrics are measures that can be used to quantify the features, characteristics and sometimes the impacts of scientific research. Historically a type of scientometric known as biblilometrics has been used to measure innovation networks--serving as a proxy for linkages among firms and their external sources of knowledge. When this knowledge underlies the firm's competitive advantage, innovation networks can be powerful predictors of innovation performance. Taking a look at the personal networks of CEO/Owner/Directors of firms might serve as an alternate to bibliometrics; where, the Ego serves as a proxy for the firm and its connections as external sources of knowledge. This approach is in line with firm resource theory and adds to the discussion about how informal networks underlie formal networks. Using ego centered network analysis sourced from the social networking site LinkedIn, the study examines the composition of European CEO networks in the pharmaceutical industry. The potential of the analysis as a new data source for innovation network studies is discussed and recommendations for its use are provided.
17 September, 2013
Hervin Fernandez Aceves (BA, Political Sciences and Public Administration & MA, Comparative History and Interdisciplinary Medieval Studies; Central European University): A Relational View of the Norman Kingdom of Sicily and its Royal Court: An Attempt to Project the Social System Constructed by ‘Hugo Falcandus’
My thesis was a study of the scope, composition, and social roles of the Norman royal court of Palermo as reported by ‘Hugo Falcandus’ in his Historia or Liber de Regno Sicilie, a narrative that relates the affairs of state and intrigues of the kingdom under William I and the first years of William II (1154-1169). The Liber, attributed to ‘Hugo Falcandus’ (pseudo-Falcandus), became a fundamental text for the understanding of the Norman kingdom of Sicily in the second half of the twelfth century. The project sought an integrative approach that would allow me to comprehend the social process and political dynamics present in the textual, narrative source. The matter upon which the study was founded were the interactions between social actors as narrated in the text (i.e. courtiers, nobles, palace servants, royal relatives) that were involved in the reported machinations. I assumed that a relational approach can contribute to the understanding of narrative sources, and the two main questions that I expected to answer were: 1) How can one extract relational data and construct networks that visualise and represent the information contained in a narrative source such as the Liber de Regno Sicilie? And 2) what do the networks this constructed tell us about the significance and implications of the social space constructed by an author such as ‘Hugo Falcandus’?
The challenge of how to ‘read’ the text hence became the main focus of my research. In order to focus on the information on social and political processes embedded in the text, I needed to transform Ps.-Falcandus’ rhetoricised periods into a relational dataset; it was necessary to place the relations, not the individuals, at the centre of the study. The first requirement of such an attempt was to present the process of translating a textual structure into a sociological construct, namely, a socio-relational dataset. After the whole Liber de Regno Sicilie was rewritten through Franzosi’s Quantitative Narrative Analysis, I obtained a dataset that divides the social information embedded in the narrative into 420 events. The total number of attested social interactions, coded as semantic triplets, is 1174, together with 89 social relationships also explicitly attested in the narrative. Each interaction and relationship defines an edge that connects two characters. The dataset thus provides a series of narrative sociomatrices ready to be parsed through network analytical tools. Although not all the resulting measures proved to be useful or provided interesting insights for understanding the Liber’s implications, the overall results are a valuable addition to the perspective of the source, and are particularly useful for providing more nuanced images of the historical text. Measures of centrality and prestige proved useful when exploring only the narrative interactions of influence and communication within the royal court. Furthermore, blockmodelling turned out to be a promising approach for understanding the entire text’s social dimensions, for the structurally equivalent positions strongly suggest the narrative roles used by the author for constructing a social system.
1 October, 2013
Ilaria Bertazzi (University of Turin, Collegio Carlo Alberto):
Debt Relationships: a Power Game. Historical Evidence and an Agent-Based model
Because of the present economic situation, especially due to the financial crisis of 2007-08, many scholars have started to investigate the nature of debt. Not only the subject, but also other problems, such as social and economic consequences related to debt have not been studied yet. Thus, in order to make better policies for decision-makers in the future, scientists have realized that it is necessary to understand how different forms of debt, such as bankruptcy are developing. In my presentation, I will show an agent-based model to describe and to understand the nature of debt, in particular household debt, which indicates that debt refusal develops as an organized movement.
8 October, 2013
Adam Tatarynowicz (Tilburg University): Environmental Demands and the Emergence of Social Structure: Technological Dynamism and Interorganizational Network Forms
This study investigates the origins of variation in the structures of global interorganizational networks across industries. We combine empirical analyses of existing interorganizational networks with an agent-based simulation model of network emergence. Our insights are twofold. First, we find that differences in technological dynamism across industries and the concomitant demands for value creation engender variation in firms’ collaborative behaviors. Specifically, firms in technologically dynamic industries on average pursue more open networks, which foster access to new and diverse resources that help sustain continuous innovation. By contrast, firms in technologically stable industries on average pursue more closed networks, which foster reliable collaboration and help preserve existing resources. Second, we show that because of the observed cross-industry differences in firms’ collaborative behaviors, the emergent industry-wide networks take on distinct global forms. Technologically stable industries feature clan networks, characterized by low global connectedness and medium-to-strong community structure. Technologically dynamic industries, by contrast, feature community networks, characterized by high connectedness and medium community structure. Convention networks, which feature high global connectedness and weak community structure, were not evident among the empirical networks we examined. The findings of this study advance an environmental contingency theory of network formation.
22 October, 2013
Péter Róbert ( Senior Research Fellow, Institute for Political Science, Centre for Social Sciences, Hungarian Academy of Sciences): Educational Segregation, Institutional Differences and Scholastic Achievement Lessons from the PISA 2003 and 2006 Data
The analysis focuses on the relationship between peer composition in school and differences in educational achievement. Research questions refer to testing two competing hypotheses: heterogeneous vs. homogeneous grouping of peers improves students’ performance. Further research questions investigate whether students with detrimental parental background benefit from studying in heterogeneous schools or students with advantageous parental background perform worse in integrated schools. The paper uses the PISA 2003 data to analyze the consequences of the various possibilities of peer compositions. Results revel that pupils’ social background has a strong impact on educational achievement. Having larger variation of peers in the school with various social backgrounds does not increase performance but students with more privileged social origin perform better in less heterogeneous schools with higher social quality.
A second analytical question is how major divisions in the school system like public–private, tracking either by curriculum or by ability, and schools’ practice regarding admittance of students affect scholastic performance. Apparently, parents consider these options when deciding about school choice. Furthermore, school’s position has an impact on students’ performance even if controlled for school composition. The results from the PISA 2006 survey indicate that high-status families prefer more selective schools with the exception of ability tracking. Moreover, the more selective schools perform better, but ability grouping does not improve achievement. Applying interaction terms shows that religious schools are able to compensate the disadvantages of pupils coming from low-status families at most.
12 November, 2013 @ CEU
Vukov Jeromos (MTA MFA KFKI): Incipient Cognition Solves the Reciprocity Conundrum of Cooperation in Structured Populations
From the simplest living organisms to human societies, cooperation among individuals emerges as a paradox difficult to explain and describe mathematically, although very often observed in reality. Evolutionary game theory offers an excellent toolbar to investigate this issue. Spatial structure has been one of the first mechanisms promoting cooperation; however, alone it only opens a narrow window of viability. Here we equip individuals with incipient cognitive abilities, and investigate the evolution of cooperation in structured populations where retaliation, forgiveness, treason and mutualism may coexist, as individuals engage in Prisoner's Dilemma games. In the model, individuals are able to distinguish their partners and act towards them based on previous interactions. In this talk, I show how the simplest level of cognition, alone, can lead to the emergence of cooperation. Despite the incipient nature of the individuals' cognitive abilities, cooperation emerges for unprecedented values of the temptation to cheat, being also robust to invasion by cheaters, errors in decision making and inaccuracy of imitation, features akin to many species, including humans.
19 November, 2013
Barta Zoltán (MTA-DE "Lendület" Behavioural Ecology Research Group): Individual Variation and Social Evolution
Life on Earth has two remarkable properties. One is variation. Apart from the vast number of extant species, considerable variation exists within species, between individuals. The other important properties of life is sociality, as Robert Trivers aptly put: "Everybody has a social life". It is surprising that until recently the interactions between these two properties have rarely been addressed from an evolutionary point of view. Here I overview studies on a special kind of individual variation: personality in insect. Then I present models which show how individual variation can affect the evolution of cooperation.
10 December, 2013
Rácz Anna, Unoka Zsolt, Soltész Péter (Semmelweis University): Micromotives and Macrobehavior in Social Networks
Many phenomena in social networks can be well explained by individual motivations and choices (micromotives in social networks). For example, trust, friendship, homophily, behavioral imitation and social learning can be described as small-scale processes with just two or a few individuals involved. However, many of these small-scale processes interconnect to large-scale social networks with specific features: Clustering, segregation and diffusion of knowledge are examples of complex large-scale structures and processes (macrobehavior in social networks) that emerge from small-scale motives and in turn have an influence on the small-scale level. In this talk, I will discuss the complex interplay between micromotives and macrobehavior in social networks. In particular, I will focus on how modern social networks research can provide new insights into this theoretical challenge by combining different methodological approaches.
27 March, 2014 @ CNS
Fabrizio Lillo (Universita' di Palermo, Italy / Santa Fe Institute, United States): Systemic price cojumps
Instabilities in the price dynamics of a large number of financial assets are a clear sign of systemic events. By investigating high cap stocks traded in different stock exchanges, we find that there is a large number of multiple cojumps, i.e. minutes in which a sizable number of stocks displays a discontinuity of the price process. By considering the last fifteen years, which have experienced the introduction of High Frequency Trading, we show that the number of jumps has slightly declined, but the number of cojumps, especially when involving a large number of stocks, has significantly increased. This is a clear sign of an increased synchronisation in financial markets. We introduce a one factor model approach where both the factor and the idiosyncratic jump components are described by a Hawkes process. We introduce a robust calibration scheme which is able to distinguish systemic and idiosyncratic jumps. Finally, we study the exogenous (i.e. news driven) and endogenous nature of systemic price cojumps and we find that only approximately one third of systemic cojumps can be associated with a macroeconomic news.
1 April, 2014 @ CEU
Boleslaw Szymanski (Rensselaer Polytechnic Institute, Troy, NY): Spread of Opinions Dynamics in Social Networks
Human behavior is profoundly affected by the influenceability of individuals and their social networks. This talk discusses the dynamics of spread of opinions in such networks using fundamental models for Social Contagion: the binary agreement model (influencing with committed minorities) and threshold model (threshold contact process). In the first one all individuals initially adopt either opinion A or B, and a small fraction of all individuals commits to their opinions. Committed individuals are immune to influence but otherwise follow the prescribed rules for opinion change. We show that the prevailing majority opinion in a population can be rapidly reversed by a small fraction of randomly distributed committed individuals. When committed individuals exist for both opinions, the difference between larger and smaller fractions of them needed for rapid majority conversion decreases as the smaller minority increases. The results are relevant in understanding and influencing the social perceptions of ideas and policies. We used the threshold model to find efficient spreaders, fast heuristic selection strategies, and impact of clustering on system dynamics. We find that even for arbitrarily high value of threshold, there exists a critical initiator fraction beyond which the cascade becomes global. Network structure, in particular clustering, plays a significant role in this scenario. Similarly to the case of single-node or single-clique initiators studied previously, we observe that community structure within the network facilitates opinion spread to a larger extent than a homogeneous random network. Finally, we study the efficacy of different initiator selection strategies on the size of the cascade and the cascade window.
8 April, 2014 @ CEU
Juraj Medzihorsky (CEU, Political Science): The mixture index of fit in social network analysis
The π* mixture index of fit is a new measure of model fit and can be applied also in social network analysis.It is easy to interpret, applies to many different models, and unlike conventional measures of fit it rests on assumptions that are always true. The index measures model fit by the smallest fraction of the population that cannot be described perfectly by a distribution belonging to the model, and facilitates new substantive findings through the analysis of the residual component. It does not depend on sample size and does not require stochastic samples, which makes it particularly appealing to use with population data. 'pistar,' an R package, allows to conveniently obtain the value of the mixture index in various settings.
22 April, 2014 @ CEU
Silvia Neamtu (CNS/CEU): Understanding Political-Business Elite Relations in Hungary through Statistical M odels for Networks
In this report, I present the preliminary findings with respect to what explains a particular network of political and business elites in Hungary. Based on a unique sample of such a network, I conduct exploratory network analysis and build statistical models to test certain ideas suggested by the descriptive analysis. I construct three Exponential Random Graph Models (ERGMs), based on alternative theoretical assertions about what generated the network of political-business ties: the social-dependence hypothesis, the cognitive consistency hypothesis, and the homophily hypothesis. The goal of the research is to understand what micro-level (actor-level) processes have generated the network we observe. ERGMs are an appropriate tool for this research problem, because they can be specified to represent multiple mechanisms that underlie the stochastic generation of the static network explored in this paper. They provide a simple and useful tool for understanding what is the probability of observing the network of interest, based on both features of the network, as well as attributes of the actors involved. The partial findings bring support in favor of the social-dependence hypothesis, suggesting that actors in the investigated network establish ties through minimizing their dependence on others and maximizing others’ dependence on them. Further research is suggested that would explore these networks over time, to uncover the complexity of political-business elite interactions. Keywords: Political networks; political-business elite relations; Hungary; ERGMs; local-global network properties
6 May, 2014 @ MTA TK
Carl Nordlund (CNS/CEU): The significance of unexpected anomalies: a deviational approach to blockmodeling of valued networks
What relations are signficant in valued networks? In order to apply the standard set of network methods to valued networks, data is typically dichotomized, i.e. where valued relations are binarized using a statistically, theoretically, or arbtrarily determined absolute threshold value. In addition to the significant loss of details this entails, dichotomization implies an implicit assumption of equal relational capacity among actors. Puerto Rican exports to USA are indeed very significant to the former, while only constituting a fraction of total US imports, distinctions that existing approaches fail to capture. This paper proposes a novel approach to role-analysis and blockmodeling of valued networks that is more sensitive to patterns, rather than mere strengths, of ties. Rather than looking at the absolute values of relations, or examining valued ties on a per-actor basis (cf Nordlund 2007), the approach specifies significance in terms of unexpected anomalies. By comparing the distribution of each actor's valued relations to its alters with the macro-level distributions of total in- and outdegrees, significant (1) and non-significant (0) ties are determined simultaneously on a per-actor-to-actor and a per-actor-from-actor basis. This allows for a direct interpretation of the underlying functional anatomy of a valued network that is explicitly concerned with patterns, rather than mere strengths, of its relations. In addition to its applicability for direct blockmodeling, the article also suggests a novel indirect measure of deviational structural equivalence that similarly identifies roleequivalence on the basis of patterns, rather than strengths, of ties. Exemplified with the notesharing data of Ziberna (2007), the EIES messages data, and total commodity trade among EU/EFTA countries as of 2010, both the direct and indirect approach yields results that, it is argued, are far more intuitive than existing approaches. This is particularly evident in the case of the EU/EFTA trade network, where the indirect approach yields partitions that reveals patterns in support of theories of intra-regional trade. Summarizing the approach and the empirical findings, the conclusion also outlines how the suggested deviational approach can be transposed into other metrics at the micro- and meso-level of networks, yielding a whole new set of traditional metrics – centrality indices, subgroup identification, density metrics etc – explicitly adapted to capture patterns in valued networks.
20 May, 2014 @ CEU
Szabolcs Számadó: The complexity of human cooperation and the five”rules”
The complexity of human cooperation is unparalleled in nature. Humans readily cooperate with non-kin, form huge societies based on cooperation and their cooperative networks can reach across the globe. Cooperation can be classified into five categories: kin selection, direct reciprocity, indirect reciprocity, network reciprocity and group selection. I would like to discuss each type, indicate their strength and weaknesses as far as modelling concerned; and discuss their relevance to human cooperation. Last but not least I would like to highlight the link between gossip and reputation on the one hand and human cooperation on the other hand.
27 May @ MTA TK
Miklós Antal (UAB Barcelona): Limits to growth from a network perspective
Whether or not long-run economic growth can be sustainable has been debated for decades. Accumulated evidence supports two important conclusions. First, all major economies are dependent on growth: if GDP declines for a longer period, then significant social tensions can be expected due to rising unemployment, falling real wages and other problems. Second, further global economic growth is very likely to be accompanied by large-scale environmental degradation. Therefore, social and environmental sustainability are likely to be incompatible. To address this dilemma, strategies are needed to decouple – as much as possible – GDP reduction from social problems and GDP growth from environmental problems. In this exploratory talk, I will look at both correlations and the prospects of decoupling from a network perspective. This can be useful because both correlations are caused, at least in part, by network-related mechanisms. For instance, social relationships that force actors to adopt competitive strategies are an important reason for the correlation between GDP reduction and social tensions. Furthermore, the correlation between GDP and environmental impacts is persistent in several fields because policy effectiveness is limited by the increasing complexity of stakeholder networks. I will discuss network-related aspects of the growth debate and highlight the possible role of the quantification of network effects in devising sustainability strategies.
10 June @ MTA TK
Renáta Németh (ELTE): Discrete Graphical Models in Social Mobility Research
Graphical models provide a well visualizable and easily interpretable representation of complex associations. The models are based on graphs in which nodes represent variables and missing edges represent conditional independence statements. These models are well suited to model direct and indirect associations and effects that are of central importance in many problems of social mobility research.
The talk provides a unified view of many of the graphical models discussed in a largely scattered literature. The marginal loglinear modeling framework proposed relies on parameters that capture aspects of associations among the variables that are relevant for the graph and, depending on the substantive problem at hand, may lead to a deeper insight than other approaches.