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Conference Paper Conference: YSM 2018. City: Balatonfüred, Hungary. Year: 2018.

The analysis of the interactional networks, collected among pre-school children (Head Start preschools, United States, data collected in 2004—2006) will be presented in order to show that the proposed symmetric core-cohesive blockmodel type can appear in such empirical networks.

A blockmodel is a network where the units are clusters of units from the studied network. The term block refers to a submatrix showing the links between two clusters. The symmetric core-cohesive blockmodel consists of three or more clusters. The units from each cluster are internally well linked while those from different clusters are ideally not linked to each other. The exception are the units from so called "core cluster". These units have a mutual links to all the units in the network. The other clusters are called "cohesive clusters".

After the analysis of the empirical networks, the presentation will address the main research question, which is whether the proposed blockmodel type can emerge as a consequence of the selected social mechanisms. The characteristics of the units are not considered. The social network mechanisms that will be considered, i.e., popularity, transitivity, mutuality and assortativity, have been extensively studied in not only interactional networks among pre-school, but also in many other types of networks. The Monte Carlo simulations are used to answer the main research question.

Conference Paper Conference: XX April International Academic Conference On Economic and Social Development. City: Moscow, Russia. Year: 2019.

Understanding patterns and underlaying mechanisms of exchanging knowledge among the employees is crucial to ensure the competitiveness of a company. Moreover, various patterns of knowledge transfer are closely related to employee performance and development. In a current study, the exchanging knowledge among the employees is called knowledge-flow. Knowledge-flow can be studied by using the social network analysis methodology. In the data collection procedure, the employees were asked to list those by whom they received different kinds of knowledge. Directed networks can be constructed based on such data. Here, nodes are employees and arrows are operationalizations of knowledge-flow.

Knowledge-flow on the level of a company can be analyzed by using blockmodeling. Blockmodeling is an approach to reduce a large, potentially incoherent networks, to a smaller and more interpretable networks. In such network, nodes represent clusters of equivalent employees.

Blockmodeling is applied on the knowledge-flow networks, collected in the middle size knowledge-based company in Slovenia (the data were collected in three time points, between 2004 and 2007). The aim is to understand the underlying mechanisms of the knowledge-flow in the company. Different mechanisms are considered: hierarchy, distance, tenure, homophily of gender, tenure and business unit and others. Based on the observations in the empirical networks, the Monte Carlo simulations are used to generate the networks by considering some selected local network mechanisms. The global network structures of the generated networks are then compared to the empirical ones.

Journal Paper Corvinus Journal of Sociology and Social Policy, Volume 9, Issue 2, Year 2018, Pages 3–24

Scientific collaboration (SC) has become a widespread feature of modern research work. While many social network studies address various aspects of SC, little attention has so far been given to the specific factors that motivate researchers to engage in SC at the individual level. In our article, we focus on the types and practices of SC that researchers in Slovenia engage in. We consider this topic by adopting a quantitative and qualitative methodological approach. The former was conducted through a web survey among active researchers, and the latter through in-depth interviews with a selected group of top researchers, i.e. intellectual leaders. Results show the extent of individual SC depends on the perceptions of researchers of the benefits of SC. Qualitative interviews additionally provide broader reflections on certain policy mechanisms that could better motivate Slovenian scientists to scientifically collaborate in the international arena.

Journal Paper Advances in Methodology and Statistics, Volume 15, Issue 1, Year 2018, Pages 1–21

Rand (1971) proposed what has since become a well-known index for comparing two partitions obtained on the same set of units. The index takes a value on the interval between 0 and 1, where a higher value indicates more similar partitions. Sometimes, e.g. when the units are observed in two time periods, the splitting and merging of clusters should be considered differently, according to the operationalization of the stability of clusters. The Rand Index is symmetric in the sense that both the splitting and merging of clusters lower the value of the index. In such a non-symmetric case, one of the Wallace indexes (Wallace, 1983) can be used. Further, there are several cases when one wants to compare two partitions obtained on different sets of units, where the intersection of these sets of units is a non-empty set of units. In this instance, the new units and units which leave the clusters from the first partition can be considered as a factor lowering the value of the index. Therefore, a modified Rand index is presented. Because the splitting and merging of clusters have to be considered differently in some situations, an asymmetric modified Wallace Index is also proposed. For all presented indices, the correction for chance is described, which allows different values of a selected index to be compared.

Journal Paper Plos ONE, Volume 13, Issue 5, Year 2018, Pages e0197514

This paper addresses the question of whether one can generate networks with a given global structure (defined by selected blockmodels, i.e., cohesive, core-periphery, hierarchical, and transitivity), considering only different types of triads. Two methods are used to generate networks: (i) the newly proposed method of relocating links; and (ii) the Monte Carlo Multi Chain algorithm implemented in the ergm package in R. Most of the selected blockmodel types can be generated by considering all types of triads. The selection of only a subset of triads can improve the generated networks’ blockmodel structure. Yet, in the case of a hierarchical blockmodel without complete blocks on the diagonal, additional local structures are needed to achieve the desired global structure of generated networks. This shows that blockmodels can emerge based only on local processes that do not take attributes into account.

Journal Paper Scientometrics, Volume 106, Issue 1, Year 2015, Pages 163-186

This article examines the structure of co-authorship networks’ stability in time. The goal of the article is to analyse differences in the stability and size of groups of researchers that co-author with each other (core research groups) formed in disciplines from the natural and technical sciences on one hand and the social sciences and humanities on the other. The cores were obtained by a pre-specified blockmodeling procedure assuming a multi-core–semi-periphery–periphery structure. The stability of the obtained cores was measured with the Modified Adjusted Rand Index. The assumed structure was confirmed in all analysed disciplines. The average size of the cores obtained is higher in the second time period and the average core size is greater in the natural and technical sciences than in the social sciences and humanities. There are no differences in average core stability between the natural and technical sciences and the social sciences and humanities. However, if the stability of cores is defined by the splitting of cores and not also by the percentage of researchers who left the cores, the average stability of the cores is higher in disciplines from the scientific fields of Engineering sciences and technologies and Medical sciences than in disciplines of the Humanities, if controlling for the networks’ and disciplines’ characteristics. The analysis was performed on disciplinary co-authorship networks of Slovenian researchers in two time periods (1991–2000 and 2001–2010).

Journal Paper Slovenian Nursing Review, Volume 48, Issue 2, Year 2014, Pages 78-87

**Introduction:** Online counselling represents a new medium for finding health information. The aim of the research is to determine the importance of analysis of adolescents' issues in order to understand their problems, needs and desires. **Methods:** In 2012 the system for the classification of questions by the type of problem was introduced. In relation to the contents the questions were first sorted to the parent category then followed by the categorization according to the subject matter. The calculation comprised the portions, averages and quartiles, and in some cases even Cramer's V coefficients. The analysis covered the entire defined population (3,257 coded questions). **Results:** Most of the users are girls (76 %), the most representative group encompasses adolescents aged between 14 and 17 years (57 %). Most questions were grouped into the categories Sexuality and sexual health (24 %), Relationships (23 %) and Body (20 %). The length of posts increases with the age of the user (Cr's V = 0.18), but differs by the gender (a higher proportion of longer questions (Cr's V = 0.15) were posted by girls) and the themes (Cr's V = 0.31). Discussion and conclusion: The categorizing of questions is suitable for the identification and analysis of adolescents' problems, needs and desires. Regular categorisation of questions with analysis will serve as a useful research tool for youth work.

Journal Paper Teorija in praksa, Volume 54, Issue 5, Year 2015, Pages 886–906

The purpose of this paper is to determine whether decision trees can be used to distinguish between those who are more and those who are less prone to depression and mental ill-being based on demographic and some other identifiable characteristics of individuals. Using decision trees we wanted to find segments which could be targeted in awarenessraising programs about depression. By analysing data from the European Social Survey in 2012 for Slovenia, we identified four groups at a greater risk of depression: young unemployed, unemployed passive, older people and women older than 52 years. Decision trees are also shown for finding target segments in the field of mental well-being. The results confirm the findings of previous studies.

Book Editors: Patrick Doreian, Vlado Batagelj and Anuška Ferligoj. Publisher: Wiley. The book is not published yet. Manuscript available at arXiv.

The paper addresses the stability of the co-authorship networks in time. The analysis is done on the networks of Slovenian researchers in two time periods (1991-2000 and 2001-2010). Two researchers are linked if they published at least one scientific bibliographic unit in a given time period. As proposed by Kronegger et al. (2011), the global network structures are examined by generalized blockmodeling with the assumed multi-core--semi-periphery--periphery blockmodel type. The term core denotes a group of researchers who published together in a systematic way with each other. The obtained blockmodels are comprehensively analyzed by visualizations and through considering several statistics regarding the global network structure. To measure the stability of the obtained blockmodels, different adjusted modified Rand and Wallace indices are applied. Those enable to distinguish between the splitting and merging of cores when operationalizing the stability of cores. Also, the adjusted modified indices can be used when new researchers occur in the second time period (newcomers) and when some researchers are no longer present in the second time period (departures). The research disciplines are described and clustered according to the values of these indices. Considering the obtained clusters, the sources of instability of the research disciplines are studied (e.g., merging or splitting of cores, newcomers or departures). Furthermore, the differences in the stability of the obtained cores on the level of scientific disciplines are studied by linear regression analysis where some personal characteristics of the researchers (e.g., age, gender), are also considered.

Book Editors: Alenka Tacol, Žarka Brišar-Slana, Brane But, Ksenija Centa, Lucija Gobov, Metka Kuhar. Publisher: National Institute of Public Health. City: Ljubljana. Year: 2014.

Knjiga Srečanja na spletu odstira več kot desetletje dolgo in bogato prakso spletnega svetovanja mladostnikom v svetovalni mreži To sem jaz, kjer ima mladostnik enostaven, anonimen, brezplačen in hiter dostop do strokovnega nasveta.

Book Publisher: Institute of Public Health of the Republic of Slovenia. City: Ljubljana. Year: 2013.

The results are comparable with previous researches and indicate the need for the introduction of contents related with sexuality in the educational process. As well, it warns on the low level of knowledge of sexual diseases and hightlights the meaning and role of the public media, especially the Internet, in the forwarding the content related to sexuality.

Bachelor's Thesis Menthors: Franc Mali and Luka Kronegger. Institution: Faculty of Social Sciences, University of Ljubljana. Year: 2013.

The thesis is founded on the findings of Slovenian and foreign authors discussing the variety of scientific activity in individual scientific disciplines. It first presents the disciplines and proceeds by studying the optimality of assessing scientific output, as defined by the Slovenian Research Agency (ARRS), based on information for the period 1985-2010 obtained using the databases SICRIS and COBISS. Scientific output is assessed through bibliographic units in individual disciplines. The findings of Ward’s method of hierarchical cluster analysis indicate that the classification proposed by the ARRS fails to reflect the specifics of bibliographic habits in given disciplines within different sciences. In addition to the specifically defined goal, the analysis reveals important information about the dynamics of the publication of various groups of Slovenian scientists.

Master's Thesis Menthor: Anuška Ferligoj. Institution: University of Ljubljana, Faculty of electrical engineering. Year: 2015.

Collaboration in science plays an important role in the production as in the dissemination of a new scientific knowledge. Even there is hard to determine the borders of scientific collaboration, the term is often operationalized through the co-authorship of scientific bibliographic units, which represents one of the most important results of a scientific collaboration. Based on the personal researchers' bibliographies, the co-authorship networks can be constructed. These networks enable us to study the relationship between some researchers' characteristics and the patterns of establishing new co-authorship ties. Furthermore, it allows us to study the structure of that kind of networks.

Kronegger et al. (2011), who studied the co-authorship networks of four scientific disciplines in four five years periods, confirmed the hypothesis about the multi-core-semi-periphery|periphery structure. In the current work, the analysis is done on the level of almost all scientific disciplines, according to the Slovenian Research Agency (ARRS). Beside the structure of co-authorship networks, the current work also addresses the question of the stability of scientific collaboration teams across scientific fields.

The structure of co-authorship networks of Slovenian researchers is examined using the pre-specified blockmodeling, while the stability of obtained clusters of researchers is measured with one of three proposed Modified Adjusted Rand Indices. In the context of co-authorship networks in two time periods, some researchers can enter or leave the network in the second time period. This implies that the classification (blockmodeling) is performed on two different sets of units for the first and for the second time period. The Modified Adjusted Rand Indices enable us to compare two clusterings, obtained on two different sets of units, where one set of units is a subset of another set of units. Moreover, the merging and splitting of clusters in time have a different effects on the value of proposed indices.

The assumed network structure multi-core-semi-periphery|periphery exists in all analysed scientific disciplines. The average core size is statistically significantlly (p < 0.05) higher in the first time period (5.6 researchers) compared to the second time period (4.4 researchers). Depending on the field, the average core size is statistically significant (p < 0.05) higher in the fields of the natural and technical sciences (4.6 researchers) that in the fields of the Social sciences and Humanities (3.8 researchers). The stability of cores on the level of scientific disciplines is relatively low. Instability of cores is more the consequence of many short term collaborations rather than splitting of cores. On the level of scientific fields, the average stability of cores is statistically significant (p < 0.05) higher in the fields of the Engineering sciences and technologies and the Medical sciences in comparison to the Humanities, while on the level of merged scientific fields into the natural and technical sciences and social sciences and humanities, there is no difference in the average stability of obtained cores (the value of MARI1 is 0.21).

Conference Paper Conference: COSTNET17. City: Palma de Mallorca, Spain. Year: 2017.

The study proposes the core-cohesive peripheries blockmodel type, consisting of one highly popular group of units and two or more cohesive groups of units. Based on the previous studies, regarding friendship networks of preschool childrens, the popularity and transitivity mechanisms are assumed to be related with the emergence of the core-cohesive peripheries blockmodel type. Therefore, two main hypotheses are tested: (i.) the core-cohesive peripheries blockmodel can emerges from random network by the influence of popularity and transitivity mechanisms, and (ii.) the core-cohesive peripheries blockmodel can emerges from random network through core-periphery, since the strength of the popularity and transitivity is assumed not to be constant in time. The hypotheses are tested using the Monte Carlo simulations. The relative criterion function is used to compare the fits of different blockmodel types on empirically generated networks.

Conference Paper Conference: CEN ISBS 2017. City: Vienna, Austria. Year: 2017.

Rand (1971) proposed what has since become a well-known index for comparing two partitions obtained on the same set of units. The index takes a value on the interval between 0 and 1, where a higher value indicates more similar partitions. Sometimes, e.g. when the units are observed in two time periods, the splitting and merging of clusters should be considered differently, according to the operationalization of the stability of clusters. The Rand Index is symmetric in the sense that both the splitting and merging of clusters lower the value of the index. In such a non-symmetric case, one of the Wallace indexes (Wallace 1983) can be used. Further, there are several cases when one wants to compare two partitions obtained on different sets of units, where the intersection of these sets of units is a non-empty set of units. In this instance, the new units and units which leave the clusters from the first partition can be considered as a factor lowering the value of the index. Therefore, a modified Rand index is presented. Because the splitting and merging of clusters have to be considered differently in some situations, an asymmetric modified Wallace Index is also proposed. For all presented indices, the correction for chance is described, which allows different values of a selected index to be compared.

Conference Paper Conference: COSTNET18. City: Warsaw, Poland. Year: 2018.

The symmetric core-cohesive blockmodel is proposed. A blockmodel is a network where the units are clusters of equivalent (according to the structure of the links) units from the studied network. The term block, in the context of blockmodels, refers to a submatrix showing the links between two clusters. The symmetric core-cohesive blockmodel consists of three or more clusters. The units from each cluster are internally well linked while those from different clusters are ideally not linked to each other. The exception are the units from so called core cluster. These units have a mutual links to all the units in the network. The other clusters are called cohesive clusters.The presentation addresses the question of whether the symmetric core-cohesive blockmodel can be found in interactional pre-school networks. To this aim, the data collected among pre-school children in Head Start preschools (United States, data collected in 2005 and 2006) are analysed. The Monte Carlo simulations are used to confirm that the selected social mechanisms (e.g., popularity, transitivity, mutuality, assortativity), defined on the local network level, can lead to the symmetric core-cohesive blockmodel global structure.

Conference Paper Conference: Applied Statistics 2018. City: Ribno, Slovenia. Year: 2018.

The core-cohesive blockmodel will be proposed in this talk. A blockmodel is one way of representing a global network structure. It is a network where the units are clusters of equivalent units from the studied network and the ties between the clusters are determined by the ties between units of two clusters. The proposed core-cohesive blockmodel type consists of one highly popular cluster and two or more cohesive clusters. The units are internally well connected in each cluster. The units belonging to the cohesive clusters are also linked to the units from the popular one.

Based on the previous studies on the network evolution, it is hypothesized that the popularity, transitivity, assortativity and mutuality mechanisms are related with the emergence of the proposed blockmodel. Therefore, the following research question will be discussed: can the core-cohesive blockmodel type emerges when subjected to the listed mechanisms? The Monte Carlo simulations are applied to this aim. Specifically, network evolution model will be used to generate networks while generalized blockmodeling will be used to assess the global network structure.

Conference Paper Conference: Networks in the Global World 2018. City: Saint Petersburg, Russia. Year: 2018.

The presentation addresses the emergence of a global network structure in kindergarten. The global network structure is defined with a blockmodel (a blockmodel is a network where the units are clusters of equivalent units from the studied network). The presentation consists of two parts. In the first part of the presentation, it is evaluated if the global network structure in an empirical interactional networks might be the symmetric core-cohesive blockmodel type. The symmetric core-cohesive blockmodel type consist of one group of units which are linked to all the other units in the network (popular group) and several cohesive groups of units which are internally linked to each other but they are also linked to the popular group. Using the Monte Carlo simulations, the question of whether the well-known mechanisms (popularity, transitivity and assortativity) can lead towards the symmetric core-cohesive blockmodel type (from random network) is addressed in the second part of the presentation.

Conference Paper Conference: SUNBELT 2018. City: Utrecht, Netherlands. Year: 2018.

A blockmodel is a network where the units are groups of equivalent units (regarding their links) from the studied network. In this talk, a new blockmodel type asymmetric core-cohesive will be proposed. This blockmodel type consists of at least three groups of units. The units from all the groups are internally linked to each other. However, a group of units to which all the others are linked (called core group or popular group) also exists. The units from the other clusters (called cohesive) are not linked. It is assumed, but not empirically confirmed, that such blockmodel type can appear in the networks of friendships among children in a pre-school class. Based on the previous studies on the evolution of such networks, the three important mechanisms are identified: the relative popularity, the transitivity and the assortativity in terms of a node's in-degree. The study addresses the question of whether the listed mechanisms can lead the global network structure towards the proposed blockmodel type. To this aim, the Monte Carlo simulations were employed. The results show that the proposed blockmodel type can appear as the consequence of the listed mechanisms, yet the global network structure is even closer to the proposed blockmodel type if the strengths of the selected mechanisms are considered to be variable in time.

Conference Paper Conference: SUNBELT 2017. City: Beijing, China. Year: 2017.

The presentation addresses the question of generating networks with a given global structure, where different global structures are defined by selected blockmodels (Wasserman and Faust 1994, Doreian et al. 2005), e.g., cohesive, core-periphery (symmetric and asymmetric), hierarchical (with and without complete blocks on the diagonal) and transitivity (with and without complete blocks on the diagonal). The networks with the given blockmodels are generated using two methods: (i.) the method of relocating of links and (ii.) the less deterministic Monte Carlo Multi Chain algorithm implemented in “ergm” package in R. Different models to generate such networks by considering triads (e.g., all existing types of triads, all allowed or all forbidden types of triads for a given blockmodel) are proposed and evaluated.

Conference Paper Conference: ARS'17. City: Naples, Italy. Year: 2017.

Based on many empirical observations and theories about social processes, several types of global structures were defined over the last 50 years by, e.g., Cartwright and Harary (1956), Davis (1967), Holland and Leinhardt (1971). The list of all allowed and forbidden types of triads for each global network structure was also proposed. Based on this, one can test the hypothesis regarding the global network structure. The presentation addresses the question of generating networks with a given global structure, where different global structures are defined by different blockmodels (Wasserman and Faust 1994, Doreian et al. 2005). To check whether only considered triads are sufficient to generate the networks with a given blockmodels, two methods are used: the method of relocating of links (RL method) and less deterministic Monte Carlo Multi Chain algorithm (MCMC algorithm) implemented in Exponential Random Graph Modeling (ERGM) R package. It can be shown that considering only different types of triads is enough to generate networks according to the most of analyzed types of blockmodels. Yet this is not true for hierarchical blockmodel structure without complete blocks on the diagonal where additional restrictions are needed.

Conference Paper Conference: COSTNET Conference. City: Ribno, Slovenia. Year: 2016.

The global structure of a network can be described by a blockmodel. There are four basic and most common blockmodels’ types: cohesive, core-periphery, hierarchy and transitivity; with some special cases such as asymmetric core-periphery and transitivity with ties between the units on the same level. On the other hand, the structure of a particular network can be described by some local network characteristics such as the distribution of different types of triangles, shared partners and other statistics. It is known that one could easily discriminate between the global structures, considering local characteristics, in the case when there are no errors in analyzed networks with a specific blockmodel structure. The current presentation will highlight the relationship between several local network characteristics and different amounts of errors in networks with different types of blockmodels.

Conference Paper Conference: Data Science and Social Research. City: Naples, Italy. Year: 2016.

Kronegger et al (2011) studied the co-authorship networks of four scientific disciplines in Slovenia and identified the most typical collaboration structure as having three basic positions: multi—core, semi—periphery and periphery. Cugmas et al (2015) confirm the assumed structure being present in all Slovenian scientific disciplines and furthermore addressed the question of the stability of obtained cores in the natural and technical sciences on one hand and the social sciences and humanities on the other.

The presentation addresses the measurement of the stability of obtained cores assuming different operationalization of the stability of cores. Therefore, several adopted Rand and Wallace indices are presented and compared based on empirical co-authorship networks of some selected Slovenian scientific disciplines in two time periods.

Conference Paper Conference: SUNBELT, International Network for Social Network Analysis. City: Brighton, UK. Year: 2015.

Recently, many studies have been performed on scientific collaboration, which is usually operationalised through co-authorship and studied by methods of social network analysis. The starting point of the presented analyses is the work of Kronegger et al. (2011) who confirmed the hypothesis of the multi-core–semi-periphery–periphery structure of a co-authorship network. The presentation addresses the measurement and explanation of the stability of cores, obtained by pre-specified blockmodeling on almost all Slovenian scientific disciplines in two time periods (1991–2000 and 2001–2010). Further, the stability of the obtained cores was measured by the proposed Modified Adjusted Rand Index 1 (MARI 1). Differences between scientific fields, controlled for some characteristics of the co-authorship network and blockmodels, were tested using linear regression.

Conference Paper Conference: SUNBELT, International Network for Social Network Analysis. City: Newport Beach, CA. Year: 2016.

Cugmas et al (2015) studied the structure of the co-authorship networks of all scientific disciplines in Slovenia. They identified the typical blockmodels’ collaboration structure as multi-core–semi-periphery–periphery. Furthermore, they tested the hypotheses regarding the differences in the stability of obtained cores between the natural and technical sciences and the social sciences and humanities.

The presentation discusses the measurement of the stability of obtained cores under different operationalization of the stability of cores. Therefore, several adopted indices for comparing two partitions (on the same and on the different sets of units) are presented and compared based on empirical co-authorship networks of some selected Slovenian scientific disciplines in two time periods.

Conference Paper Conference: IFCS International Federation of Classification societies. City: Bologna, Italy. Year: 2015.

Rand (1971) proposed the Rand Index to measure the stability of two partitions of one set of units. Hubert and Arabie (1985) corrected the Rand Index for chance (Adjusted Rand Index). In this paper, we present some alternative indices. The proposed indices do not assume one set of units for two partitions. Here, one set of units can be a subset of the other set of units. According to the purpose of the comparison of two partitions, the merging and splitting of clusters in two partitions can have different impact on the value of the indices. Therefore, we proposed different modified Rand Indices.

Conference Paper Conference: 11th Applied Statistics 2014. Statistical Society of Slovenia. City: Ribno, Slovenia. Year: 2014.

The scientific collaboration networks of Slovenian researchers at the level of scientific disciplines during two ten-year time periods (from 1991 to 2000 and from 2001 to 2010) are studied. The collaboration is defined as co-authorship of one or more published outputs that Slovenian Research Agency (ARRS) evaluates as scientific works.

The analysis is based on the work of Kronegger et al (2011), who studied the co-authorship networks of four scientific disciplines in Slovenia and proposed the most typical form of collaboration structure that consists of multi core - semi-periphery - periphery. Based on their study, we applied pre-specified blockmodeling to the most of the scientific disciplines (we excluded those disciplines with too small number of the researchers in them). In the presentation we will discuss the problem of determining the optimal number of clusters and the local optimization problem to determine structurally equivalent clusters. We will graphically present the dynamics of the collaborating groups over time obtained by the blockmodeling procedure.

To measure the transitions between two time periods or the stability of obtained clusterings we used Adopted Rand Index. To explain the obtained transitions by the characteristics of the co-authorship networks (e.g., the number of researchers in the discipline, average number of co-authors of the researchers in the discipline, the rate of change of the number of researchers, the rate of change of density of the network), the characteristics of the obtained block structures (e.g., the number of core clusters, the proportion of the periphery, the number of bridging cores) and the characteristics of the disciplines will be used.

Conference Paper Conference: 11th Applied Statistics 2014. Statistical Society of Slovenia. City: Ribno, Slovenia. Year: 2014.

Co-authorship as form of scientific collaboration presents the major interaction mechanism between actors at the micro-level of individual scientists. Wide range of mechanisms fostering collaboration produce different structures within general network. The dynamic nature of co-authorship networks presents an interesting problem when trying to analyze the properties of established, emerging and dissolving groups of co-authoring researchers in time.

To analyze the properties of structure dynamics we used blockmodeling method (structural equivalence) with following of individual researchers through time (Kronegger et. al 2011), and stochastic actor based modeling of network dynamics (Siena). In Siena we used two approaches to modeling the effect of structural equivalence to formation of ties within the network: i) including the “balance effect” (Ripley et. al 2013) which is included in predefined set of Siena effects and ii) including the information on structural equivalence on dyadic level using dissimilarity matrix as explanatory variable.

In our research we observed and compared collaborative structures in complete longitudinal co-authorship networks for selected disciplines. Dataset gathered from national bibliographic system COBISS, spanning from 1996 to 2010, was split into three consecutive five-year intervals.

Conference Paper Conference: 12th Applied Statistics 2015. Statistical Society of Slovenia. City: Ribno, Slovenia. Year: 2015.

The Rand Index (Rand 1971) is one of the most commonly used indices for measuring the stability of two partitions of one set of units. In some cases, there is a need to compare two partitions obtained on two sets of units, where one set is a subset of another set of units. The merging and splitting of clusters can have different impacts on the value of the indices when comparing two partitions. Therefore, we propose different modified Rand Indices. In addition, we also suggest the adjustment for chance for all proposed indices, which can be obtained by simulations. Some examples of comparing partitions obtained on different sets of units is also given.

Conference Paper Conference: 12th Applied Statistics 2015. Statistical Society of Slovenia. City: Ribno, Slovenia. Year: 2015.

In presented analysis we made a step closer towards combining two methodological approachies of social network analysis: well established method of blockmodeling based on works of Lorrain & White (1971) and Doreian et al. (2005), and relatively new approaches to stochastic actor based modeling of network dynamincs presented by Snijders (2001, 2005) and Snijders et al. (2007, 2010). Combination of two methods offers a great opportunity for analysis of influence of individual and group characteristics on the dynamics of emergent structure in the network. Presented analysis is performed on data of collaboration networks of Slovenian researchers measured in period from 1996-2010, sliced in to two consecutive 10-year time spans.

Conference Paper Conference: 13th Applied Statistics 2016. Statistical Society of Slovenia. City: Ribno, Slovenia. Year: 2016.

Blockmodeling, as a method to reduce a large and potentially incoherent networks to a smaller and less complex networks (Doreian et al. 2005), differ from community detection methods since blockmodeling allows not only to detect highly connected groups of units, but also the relations between the obtained group of units (de Nooy et al. 2011). Therefore, blockmodeling is seen as appropriate method to describe the global structure of a certain network. The most known structures are cohesive, center-periphery, hierarchy and transitivity (Doreian et al. 2005).

The micro-level processes that might drive the evolution of a network towards a given blockmodel are studied. To this aim, the Exponential Random Graph Modeling is used. The addressed research objective is especially important in the context of studying the evolution of different types of networks.

Conference Paper Conference: ARS'15 International Workshop and ARS'15 Short Course. City: Capri, Italy. Year: 2015.

The abstract is temporarily unavailable

Conference Paper Conference: Young Statisticians Meeting. City: Vorau, Austria. Year: 2015.

Rand (1971) proposed well-known index for comparing two partitions obtained on the same set of units. The index takes the value on the interval between 0 and 1, where a higher value indicates more similar partitions. The index is symmetric in the sense that both splitting and merging of clusters lower the value of the index. Sometimes, e.g. when the units are observed in two time periods, the splitting and merging of clusters should be considered differently, according to the operationalization of stability of clusters. In that case the Wallace index B' (Wallace 1983) can be used. Furthermore, there are several cases when one would want to compare two partitions obtained on the different sets of units, where one is a subset of another. In that case, the new units and units which leave the clusters from the first partition can be considered as a factor lowering the value of the index. Therefore, two modified Rand indices will be presented, along with its correction for chance, which allow comparing different values.

Conference Paper Conference: SRA (Society for Research on Adolescence) Biennial Meeting. City: Minneapolis, Minnesota. Year: 2018.

Research aimed at understanding the dynamics of peer relationships must consider two important points: (1) the complexity of interpersonal relationship dynamics and (2) the complexity of structural constraints, such as classrooms and schools, on peer relationship dynamics. Such investigations also present statistical challenges that require the application of innovative methodologies, including data simulation, multilevel modeling, and social network analysis. Thus, this symposium aims to discuss some critical methodological considerations, as well as real world implications for the role of peer network structure in child and adolescent development.

To this end, three papers will be presented that describe how developmental scholars might think about and conceptualize peer network structures using advanced methodological techniques (e.g., simulation, multilevel, social network analysis) in order to address important developmental questions (e.g., bullying, helping behavior). Three presentations from international scholars in the Netherlands, Slovenia, and the USA make up this symposium. The first presentation describes the dynamics behind the creation of peer network structure using simulated social network data. The second presentation builds upon this study by considering how multilevel models can be used to understand the impact of peer network structure at the individual and classroom level, as it relates to important developmental outcomes (e.g., bullying). The third presentation discusses the need to consider multiple and overlapping interactions between specific forms of social network structures (e.g., friendship and helping networks). Discussions consider the significant role of developing peer network structures throughout childhood and adolescence.

Conference Paper Conference: NetSlo'18. City: Ljubljana, Slovenia. Year: 2018.

Predstavitev naslavlja vprašanje zmožnosti generiranja omrežij s točno določeno globalno strukturo zgolj z upoštevanjem lokalnih podstruktur. Različne globalne strukture omrežij so operacionalizirane z različnimi vrstami bločnih modelov. Bločni model je omrežje, kjer so enote skupine enakovrednih enot opazovanega omrežja. Pri tem se omejimo na strukturno enakovrednost (dve enoti sta strukturno nakovredni, če sta enako povezani z ostalimi enotami). V analizi preučujemo najbolj znane vrste bločnih modelov: koheziven, center-periferija, tranzitiven in hierarhičen tip bločnega modela. Lokalne strukture omrežij predstavljajo različne vrste triad. Za generiranje omrežij sta uporabljena algoritem prestavljanja povezav in Monte Carlo Multi Chain algoritem, implementiran v programski paketek »ergm« programskega jezika R. Rezultati kažejo, da je, zgolj z upoštevanjem različnih vrst triad, mogoče generirati omrežja različnih globalnih struktur, a vključitev dodatnih lokalnih struktur (na primer poti dolžine tri) lahko znatno pripomore k nastanku želene globalne strukture. Pri generiranju tovrstnih omrežij ne upoštevamo lastnosti enot.

Conference Paper Conference: International Statistical Conference in Croatia (ISCCRO’16) City: Zagreb, Croatia. Year: 2016.

Rand Index (Rand 1971) is used to compare two partitions obtained on the same sets of units, where merging and splitting of clusters are seen as factors which lower the value of the index (the index can take the value on the interval between 0 and 1 where higher value indicates more similar partitions). In some research problems, the splitting and merging of clusters have to be considered as factors with different effects on the value of an index. In such cases one of the Wallace indices can be used (Wallace 1983). Here only the merging or only the splitting of groups lowers the value of an index. The presentation addresses the case when two partitions are obtained on two different sets of units with a non-empty intersection (e.g., when the sets of units are obtained in two different time points). In such cases the in-coming and out-going units are usually present and considered as factors which indicates lower level of stability (or similarity) of two partitions. Therefore, the two modified Rand indices and two Wallace indices are presented along with the correction for chance, which enables to compare the values of indices obtained on different partitions.

Conference Paper Conference: 48th Scientific Meeting of the Italian Statistical Society (SIS2016) City: Salerno, Italy. Year: 2016.

Kronegger et al (2011) studied the co-authorship networks of four scientific disciplines in Slovenia and identified the most typical collaboration structure as having three basic positions: multi—core, semi—periphery and periphery. Cugmas et al (2015) confirmed the assumed structure being present in all Slovenian scientific disciplines and furthermore addressed the question of the stability of obtained cores. The presentation addresses the measurement of the stability of obtained cores assuming different operationalization of the stability of cores. Several adopted Rand and Wallace indices are presented and compared based on empirical co-authorship networks of some selected Slovenian scientific disciplines in two time periods.

Conference Paper Conference: Second European Conference on Social Networks. City: Paris, France. Year: 2016.

"The aim of a blockmodeling is to reduce a large potentially incoherent network to smaller and less complex network (Doreian et al. 2005)". In comparison with community detection methods, blockmodeling allows not only to detect highly connected groups of units, but also the relations between the obtained groups of units (de Nooy et al. 2011). Therefore, blockmodeling is seen as appropriate method to describe the structure of a certain network. The most known structures of blockmodels are center-periphery, hierarchy, cohesion and others (Doreian et al. 2005). Studies done on empirical networks show that the network's structure can move from one to another blockmodel type in time under the in uence of some factors (e.g. the blockmodel of center-periphery type can move to a complete network, where all nodes are linked) (Bettencourt et al 2009, Kronegger et al 2015). The presentation addresses the factors that a ect the transition from one type of a blockmodel to another type of a blockmodel.

Invited Lecture Host: Faculty of information studies. City: Novo mesto, Slovenia. Year: 2018.

Pogovarjali se bomo o zmožnosti generiranja omrežij s točno določeno globalno strukturo - zgolj z upoštevanjem lokalnih podstruktur. Lastnosti enot ne bomo upoštevali.

Različne globalne strukture omrežij bomo operacionalizirali z različnimi vrstami bločnih modelov. Bločni model je omrežje, kjer so enote skupine enakovrednih (glede na strukturo povezav) enot opazovanega omrežja. Za lažjo predstavo o bločnih modelih in bločnem modeliranju, kot postopku za določitev bločnega modela v empiričnih omrežjih, si bomo pogledali nekaj pristopov k bločnemu modeliranju na empiričnih primerih so-avtorskih omrežij. Kot lokalne podstrukture omrežij bomo obravnavali različne vrste triad.

Za generiranje sintetičnih omrežij bomo uporabili algoritem prestavljanja povezav in Monte Carlo Multi Chain algoritem, implementiran v programski paketek "ergm" programskega jezika R. Pokazali bomo, da je mogoče z upoštevanjem različnih vrst triad generirati omrežja različnih globalnih struktur, a vključitev dodatnih lokalnih struktur lahko znatno pripomore k nastanku želene globalne strukture.

Invited Lecture Host: Institute for Biostatistics and Medical Informatics. City: Ljubljana, Slovenia. Year: 2016.

Rand Index (Rand 1971) is known as one of the most common indices for comparing two partitions obtained on the same sets of units. It can take the value on the interval between 0 and 1 where higher value indicates more similar partitions. When measuring the similarity of two partitions the splitting and merging of clusters can be considered as factors with different effects on the value of an index. The Rand Index belongs to a group of symmetric indices in this context since both merging and splitting have a negative effect on the value of the measure. When the splitting and merging of groups have to be considered differently - according to the operationalization of studied groups - one of the Wallace indices can be used (Wallace 1983). Here, only the merging or only the splitting of groups lowers the value of an index.

In the case when two partitions are obtained on two different sets of units with a non-empty intersection, the number of in-coming and out-going units (e.g., when the sets of units are obtained in different time points) can be considered as a factors which lowers the value of an index. Therefore the two symmetric modified Rand indices and two asymmetric Wallace indices will be presented along with the correction for chance, which enables to compare the values of indices obtained on different partitions.

Invited Lecture Host: Faculty of Mathematics and Physics. City: Ljubljana, Slovenia. Year: 2015.

Bločno modeliranje omogoča reduciranje velikih, nekoherentnih omrežij v manjša in razumljivejša omrežja, ki jih je lažje interpretirati. Na tokratnem sredinem seminarju bomo predstavili rezultate bločnega modeliranja so-avtorskih omrežij slovenskih raziskovalcev v dveh časovnih obdobjih (1991-2000 in 2001-2010) na ravni znanstvenih disciplin, kot jih opredeljuje Javna agencija za raziskovalno dejavnost RS.

Za merjenje stabilnosti skupin raziskovalcev bomo izhajali iz Adjusted Rand Index (ARI), ki se uporablja za primerjanje dveh razvrstitev, izračunanih na isti množici enot. V kontekstu preučevanja so-avtorskih omrežij v dveh časovnih obdobjih, pa enote navadno prihajajo v omrežje (npr. mladi raziskovalci) ali ga zapuščajo (npr. upokojitev), kar pomeni, da je razvrščanje (bločno modeliranje) v prvem in v drugem časovnem obdobju izvedeno na dveh različnih množicah enot. Predstavljene različne prilagoditve ARI-ja omogočajo primerjanje razvrstitev, kjer je ena množica enot za razvrščanje podmnožica druge množice enot. Združevanje in deljenje skupin raziskovalcev prav tako različno vplivata na vrednosti tako prilagojenih ARI-jev.

V zaključku bomo predstavili izračunane vrednosti ene izmed različic prilagojenih ARI-jev za vse analizirane znanstvene discipline.

Invited Lecture Host: Faculty of Mathematics and Physics. City: Ljubljana, Slovenia. Year: 2016.

Glede na empirične podatke in različna teoretična izhodišča, so raziskovalci definirali različne tipične globalnih struktur omrežij, na primer model 'ballance' (Cartwright in Harary 1956), model 'clustering' (Davis 1967) in model 'transitivity' (Holland i Leinhardt 1971). Davis in Leinhardt (1967) sta predstavila klasifikacijo vseh možnih tipov grafov velikosti tri in v okviru slednje je nastal seznam prepovedanih in dovoljenih tipov trikotnikov za omenjene globalne strukture. Davis in Leinhardt (1970) sta ugovarjala, da je zaradi možnosti prisotnosti napak v omrežju potreben manj deterministični pristop k ugotavljanju globalnih struktur. Tako sta, na podlagi porazdelitev trikotnikov v slučajih omrežjih, zasnovala teste za preverjanje domnev o številu prepovedanih in dovoljenih tipov trikotnikov v empiričnih omrežjih.

Na tokratnem Sredinem seminarju bomo globalno strukturo omrežij definirali z različnimi tipi bločnih modelov (koheziven, tranzitiven, center-periferija, hierarhičen), poleg različnih tipov trikotnikov pa bomo preučevali tudi nekaj drugih lokalnih značilnosti omrežij. Pokazali bomo, katere statistike, povezane z lokalnimi značilnostmi omrežij so enake 0 v primeru omrežij brez napak in nadalje, kako različni deleži napak v omrežju vplivajo na te statistike. Glede na slednje bomo izbrali tiste lokalne značilnosti omrežij, ki jih je potrebno upoštevati pri generiranju slučajnih omrežij, da bi dobili določeno globalno strukturo omrežja. V okviru tega bomo predstavili dva načina simuliranja omrežij z določeno globalno strukturo: bolj determinističen iterativni postopek s prestavljanjem povezav in, v okviru Exponential Random Graph Modeling (ERGM), manj deterministični Monte Carlo Multi Chain algoritem.

Zgolj na podlagi informacije o prepovedanih tipih trikotnikov (ob predpostavljeni fiksni gostoti) je mogoče generirati skoraj popolna omrežja z različnimi globalnimi strukturami, kar pa ne velja za hierarhični model z več skupinami, kjer so potrebne dodatne omejitve.

Invited Lecture Host: Faculty of Mathematics and Physics. City: Ljubljana, Slovenia. Year: 2016.

V drugem delu seminarja bomo na hitro ponovili pojme iz prvega dela, ki so potrebni za razumevanje drugega dela. V drugem delu bomo spoznali algoritme za generiranje omrežij z izbrano globalno strukturo.

Glede na analize iz prvega dela bomo izbrali tiste lokalne značilnosti omrežij, ki jih je potrebno upoštevati pri generiranju slučajnih omrežij, da bi dobili določeno globalno strukturo omrežja. V okviru tega bomo predstavili dva načina simuliranja omrežij z določeno globalno strukturo: bolj determinističen iterativni postopek s prestavljanjem povezav in, v okviru Exponential Random Graph Modeling (ERGM), manj deterministični Monte Carlo Multi Chain algoritem.

Zgolj na podlagi informacije o prepovedanih tipih trikotnikov (ob predpostavljeni fiksni gostoti) je mogoče generirati skoraj popolna omrežja z različnimi globalnimi strukturami, kar pa ne velja za hierarhični model z več skupinami, kjer so potrebne dodatne omejitve.

Invited Lecture Host: Faculty of Mathematics and Physics. City: Ljubljana, Slovenia. Year: 2017.

Bločni model je omrežje, kjer so vozlišča skupine enakovrednih enot (glede na povezave z ostalimi enotami). Med bolj znane tipe bločnih modelov sodita kohezivni in center-periferija. Prvi navadno sestoji iz nekaj skupin, ki so znotraj dobro povezane, med enotami iz različnih skupin pa ni povezav. Po drugi strani pa tip center-periferija sestoji iz dveh skupin, kjer so enote iz prve skupine (popularne enote) med sabo dobro povezane, enote iz druge skupine (periferne enote) pa med sabo niso povezane. Periferne enote so povezane s popularnimi enotami.

Na tokratnem sredinem seminarju bomo predstavili bločni model, ki je nekakšna kombinacija zgoraj navedenih tipov bločnih modelov: center-periferija kohezivni tip bločnega modela. Ta sestoji iz ene skupine popularnih enot in več skupin kohezivnih enot. Enote iz kohezivnih skupin so povezane s popularnimi enotami. Na podlagi predhodnih raziskav, s področja razvoja omrežij prijateljstev med otroci v vrtcih, bomo preverili, ali lahko izbrani mehanizmi (popularnost, asortativnost in tranzitivnost) vplivajo na nastanek center-periferija kohezivnega tipa bločnega modela.

Invited Lecture Host: Higher School of Economics, National Research University. City: Moscow, Russia. Year: 2019.

In the first part of the presentation, different indices for comparing two partitions are presented (Cugmas, Ferligoj 2018). They are based on the Rand index (Rand 1971) and Wallace indices (Wallace 1983) which are used to compare the stability (or similarity) of two partitions, obtained on the same set of units. In the case of the Rand index merging and splitting of clusters indicate lower stability while in the case of Wallace indices only splitting or only merging of clusters indicates lower stability of clusters. Let us assume that one set of units was observed at the first time point while the second set was observed at the second time point. In this case some units join at the second time point or/and some units leave at the second time point. One has to decide how to consider these units. Therefore, different modifications of Rand index and Wallace indices are proposed. For all indices, the correction for chance is described (this allows different values of a selected index to be compared).

In the second part, the structures of co-authorship networks are examined by using the pre-specified blockmodeling approach (Doreain et al. 2005). The multi-core—semi-periphery—periphery (Kronegger et al. 2011) blockmodel type is described in this presentation and used in the pre-specified blockmodeling. The analyses are done on the co-authorship networks for each scientific discipline as defined by the Slovenian Research Agency. The nodes represent authors and the links between the nodes operationalize co-authorship of at least one scientific bibliographic unit. The data for two time periods are considered (1991–2000 and 2001–2010). Different scientific disciplines are compared regarding the number of authors, the density of the obtained networks, the number of cores, the size of the periphery etc. The obtained co-authorship networks are also visualized in line with the obtained blockmodels.

In the third part of the presentation, the proposed indices are used to measure the stability of the obtained blockmodels. A special attention is given to the stability of the cores. A core is a group of authors which co-author in a more systematic way with each other than with the others in the network. Different factors, which are assumed to affect the stability of cores, are used to analyze the source of (in)stability of scientific disciplines and to explain the differences in the stability of scientific disciplines.

The presentation is based on the chapter Scientific co-authorship networks which will appear in the book Advances in Network Clustering and Blockmodeling (edited by Doreain et al., published by Wiley in 2019).

Invited Lecture Host: Faculty of Mathematics and Physics. City: Ljubljana, Slovenia. Year: 2019.

Understanding patterns and underlaying mechanisms of exchanging knowledge among employees is crucial to ensure their professional development and consequently competitiveness of a company. Exchanging knowledge of different types can be operationalized by so called knowledge-flow networks. In such networks, nodes represent employees and links among them are measured by the flow of different kinds of knowledge.

The presentation will consist of two parts. In the first part, the analysis of the data, collected among the employees of a middle size Slovenian company, will be presented (Miha Škerlavaj, 2007). The data were collected at three time points (2004, 2006 and 2007). The generalized blockmodeling (Doreian, Batagelj, & Ferligoj, 2005) was used to reveal the global network structures of the knowledge-flow networks. Then, different types of indices for measuring the similarity of two partitions (Cugmas & Ferligoj, 2018) were used to explain the stability of the obtained blockmodels in time and finally, different attributes (characteristics of the employees, e.g., gender, tenure, …) were considered to describe the mechanisms that might cause the observed dynamics of the global network structure.

The algorithm for generating knowledge-flow networks (by considering different local network mechanisms) will be presented in the second part of the presentation. The algorithm and the corresponding mechanisms are defined based on the theory proposed by Nebus (2006). Here, advice-seekers consider the cost of obtaining advice from a given employee on one hand and the potential value of the employees’ advice on the other hand. Different types of the perceived costs and the perceived values are operationalized by different local network mechanisms. The Monte Carlo simulations were used to test which local network mechanisms are necessary to obtain a hierarchical blockmodel with complete blocks on the diagonal.

Literature

Cugmas, M., & Ferligoj, A. (2018). Comparing two partitions of non-equal sets of units. Advances in Methodology and Statistics, 15(1), 1–21.

Doreian, P., Batagelj, V., & Ferligoj, A. (2005). Generalized blockmodeling (Vol. 25). Cambridge: Cambridge university press.

Nebus, J. (2006). Building collegial information networks: A theory of advice network generation. Academy of Management Review, 31(3), 615–637.

Škerlavaj, Miha. (2007). The network perspective and performance of organizational learning: Theoretical and empirical analysis. Ljubljana: University of Ljubljana.

Invited Lecture Host: Faculty of Mathematics and Physics. City: Ljubljana, Slovenia. Year: 2018.

Bločni model je omrežje, kjer so vozlišča skupine enakovrednih enot (glede na povezave z ostalimi enotami). Na enem izmed preteklih Sredinih seminarjev smo predstavili tako imenovan (simetričen in asimetričen) središčno-kohezivni tip bločnega modela. Ta sestoji iz skupine popularnih enot in več kohezivnih enot, ki so povezane s popularnimi enotami. Popularne enote so povezane z enotami iz kohezivnih skupin, ko gre za asimetrični tip bločnega modela, poleg slednjega pa so enote iz kohezivnih skupin povezane tudi s popularnimi enotami, ko gre za simetričen tip bločnega modela. Za asimetrično različico smo pokazali, da lahko nastane kot posledica mehanizmov popularnosti, asortativnosti in tranzitivnosti. Ti so pogosto upoštevani pri modeliranju omrežij prijateljstev med predšolskimi otroki.

Na tokratnem sredinem seminarju bomo preverjali, ali je simetričen središčno-koheziven tip bločnega modela prisoten v omrežjih interakcij med otroki v vrtcih. V ta namen bomo analizirali omrežja, ki so bila zbrana med predšolskimi otroki v letih med 2005 in 2008 v Združenih državah Amerike. V takem omrežju sta otroka povezana, če sta bila opažena med skupnim igranjem. Podatki so bili zbrani v okviru večje longitudinalne raziskave, analizirani pa tudi z uporabo SIENA modelov (Schaefer et al. 2010).

Schaefer, D. R., Light, J. M., Fabes, R. A., Hanish, L. D., & Martin, C. L. (2010). Fundamental principles of network formation among preschool children. Social Networks, 32(1), 61-71.

Conference Paper Conference: 7th South Eastern European and Adriatic Drug Addiction Treatment Conference and 14th SEEAnet Symposium on Addictive Behaviours and 6. slovenski simpozij o okužbi z virusom hepatitisa C pri osebah, ki uživajo droge. City: Ljubljana, Slovenia. Year: 2015.

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