Generating global network structures by triad types

This paper addresses the question of whether it is possible to 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 method of relocating links; and (ii) the Monte Carlo Multi Chain algorithm implemented in the "ergm" package implemented in R. Although all types of triads can generate networks with the selected blockmodel types, the selection of only a subset of triads improves the generated networks' blockmodel structure. However, 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 on only local processes that do not take attributes into account

The stability of co-authorship structures

This article examines the structure of co-authorship networks\u27 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\u27 and disciplines\u27 characteristics. The analysis was performed on disciplinary co-authorship networks of Slovenian researchers in two time periods (1991-2000 and 2001-2010)

The personal factors in scientific collaboration: views held by Slovenian researchers

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

Socialna opora starejših, ki živijo v domačem okolju, v času prvega vala epidemije koronavirusa v Sloveniji

Slovenija sodi med hitro starajoče se države, kar zahteva prilagoditve družbe na različnih področjih. Eno izmed njih je skrb za starejše, ki zaradi težav, povezanih s staranjem, potrebujejo vrsto storitev in pomoči. Del potrebne pomoči lahko pokrijejo formalne storitve (kot je osebna pomoč na domu), zelo pomembni pa so tudi neformalni viri socialne opore (sorodniki, prijatelji, sosedi). Raziskave kažejo, da ima del starejših razmeroma zadostno socialno oporo, obstaja pa tudi nezanemarljiv delež starejših s šibko socialno oporo ali brez virov neformalne socialne opore. Ti so lahko še posebej ranljivi v okoliščinah, kot je pandemija koronavirusa SARS-CoV-2. Tako članek naslavlja značilnosti omrežij socialne opore starejših, ki živijo doma, v času popolnega zaprtja javnega življenja v prvem valu pandemije, in sicer na podlagi podatkov, zbranih v okviru spletnega panela JazVem. Gre za verjetnostni vzorec 605 oseb, starejših od 64 let. V raziskavi so bile merjene čustvena in instrumentalna opora, opora v smislu neformalnega druženja, pa tudi elementi formalne opore in različne značilnosti omrežij. V vzorcu je bila dobra desetina starostnikov z omejenimi viri socialne opore. To so starostniki, ki niso navedli nobenega vira socialne opore, in starostniki s samo oddaljenimi viri socialne opore. Na število in dostopnost virov socialne opore v času pandemije vplivata spol in velikost gospodinjstva starostnika

Local Mechanisms Affecting the Evolution of Blockmodels

Raziskovalci s področja družboslovja želijo pogosto razumeti odnos med družbenimi mikromehanizmi in družbenim makroizidom. V okviru analize omrežij so različni družbeni mikromehanizmi navadno operacionalizirani z lokalnimi omrežnimi mehanizmi, družbeni izidi na makroravni pa so operacionalizirani z različnimi globalnimi zgradbami omrežja (Stadtfeld, 2018). Tako je namen pričujoče disertacije proučiti odnos med lokalnimi omrežnimi mehanizmi in globalnimi omrežnimi zgradbami. Poleg nastanka izbranih vrst globalnih omrežnih zgradb je naslovljen tudi prehod iz ene v drugo globalno zgradbo omrežja. Različne vrste globalnih zgradb omrežij so opredeljene z različnimi vrstami bločnih modelov. Bločni model je definiran kot omrežje, v katerem so vozlišča skupine enakovrednih (glede na zgradbo povezav) vozlišč proučevanega omrežja, povezave pa so povezave med skupinami in znotraj skupin. Izraz »blok« se nanaša na matriko povezav, ki prikazuje povezave med vozlišči iz dveh različnih skupin ali med vozlišči znotraj ene skupine (Doreian in drugi, 2005). Tako kot različne globalne zgradbe omrežij je tudi družbene mehanizme mogoče opredeliti na različne načine. Skupna mnogim opredelitvam je trditev, da ima upoštevanje družbenih mehanizmov zelo pomembno vlogo pri pojasnjevanju družbenih pojavov (Hedström in Swedberg, 1998). Stadtfeld (2018) in Hedström in Swedberg (1998) so opredelili tri vrste mehanizmov: situacijske mehanizme (nanašajo se na vpliv globalne omrežne zgradbe na lastnosti posameznika, na primer na njegove želje, prepričanja in možnosti), vedenjske mehanizme (nanašajo se na to, kako lastnosti posameznika vplivajo na njegovo vedenje) in pretvorbene mehanizme (nanašajo se na to, kako vedenje posameznika vpliva na globalno omrežno zgradbo). V tej disertaciji so naslovljeni vedenjski ter pretvorbeni mehanizmi, ki jih je mogoče operacionalizirati prek množice pravil o vzpostavljanju, vzdrževanju in prekinjanju povezav. Disertacija je urejena v dveh delih. Zmožnost generiranja omrežij z izbrano vrsto bločnega modela, z upoštevanjem različnih vrst tirad, je naslovljena v prvem delu disertacije. To raziskovalno vprašanje je pomembno zlasti zato, ker še ni raziskave, ki bi sistematično naslovila povezavo med različnimi vrstami triad in različnimi vrstami bločnih modelov. Zmožnost generiranja omrežij z izbranimi vrstami bločnih modelov, brez upoštevanja lastnosti vozlišč, kaže, da lahko izbrane vrste bločnih modelov nastanejo kot rezultat izbranih lokalnih mehanizmov, kot so mehanizem popularnosti, mehanizem podobnosti stopenj, mehanizmi, povezani s tranzitivnostjo, in ostali. Za namene prvega raziskovalnega vprašanja so različne vrste triad razvrščene v množico dovoljenih ali v množico prepovedanih vrst triad. Takšna klasifikacija je narejena za vsako obravnavano vrsto bločnih modelov. Dana vrsta triade je dovoljena, če je njena frekvenca v omrežju z izbranim bločnim modelom brez napak večja od 0, sicer pa je prepovedana. Algoritem prestavljanja povezav (algoritem RL) ter algoritem MCMC sta bila uporabljena za generiranje omrežij z upoštevanje prepovedanih in/ali dovoljenih vrst triad. Z upoštevanjem različnih vrst triad je mogoče generirati večino analiziranih vrst bločnih modelov. To nakazuje, da se različne vrste bločnih modelov lahko pojavijo kot posledica lokalnih omrežnih mehanizmov, ki so neodvisni od lastnosti vozlišč. Drugi del disertacije obravnava lokalne omrežne mehanizme namesto lokalnih omrežnih zgradb, v okviru različnih vrst bločnih modelov. Medtem ko so lokalne omrežne zgradbe opredeljene z različnimi vrstami podomrežij, so lokalni omrežni mehanizmi procesi, ki vplivajo na konkretna dejanja vozlišč v omrežju, kot je to opisano v prejšnjih odstavkih. Različni lokalni omrežni mehanizmi so opredeljeni z različnimi omrežnimi statistikami, kar je upoštevano v algoritmih NEM. Ker obstaja veliko vrst bločnih modelov in lokalnih omrežnih mehanizmov, je za izbiro lokalnih omrežnih mehanizmov in pripadajočih vrst bločnih modelov dobro upoštevati izbrane družbene kontekste. V tej raziskavi sta upoštevana naslednja družbena konteksta: (i) prijateljstva in naklonjenosti med predšolskimi otrokiter (ii) pretok znanja med zaposlenimi v podjetju, ki temelji na znanju. Na osnovi navedenih družbenih kontekstov sta predlagani dve vrsti bločnih modelov: (simetričen ter asimetričen) središčno-koheziven bločni model ter hierarhično-koheziven bločni model z nekohezivno zadnjo skupino. V disertaciji je pokazana smiselnost obravnave obeh vrst bločnih modelov v okviru družbenih kontekstov, ki so povezani z vrtci ali s podjetji. Rezultati Monte Carlo simulacij kažejo, da lahko (simetričen in asimetričen) središčno-kohezivni bločni model nastane kot posledica mehanizmov vzajemnosti, popularnosti, podobnosti stopenj in mehanizmov, povezanih s tranzitivnostjo. To velja za vse obravnavane začetne zgradbe omrežij: prazno omrežje, omrežje s kohezivnim bločnim modelom ter omrežje z asimetričnim središčno-perifernim bločnim modelom. V disertaciji je pokazano (na osnovi že obstoječih podatkov, zbranih v ZDA), da se simetrična središčno-kohezivna vrsta bločnega modela pojavlja v omrežjih interakcij med predšolskimi otroki. To, da je mogoče omrežja s tako vrsto bločnega modela generirati z upoštevanjem navedenih lokalnih omrežnih mehanizmov, še ne pomeni, da so globalne zgradbe v empiričnih omrežjih nastale kot posledica analiziranih (v simulacijski študiji) lokalnih omrežnih mehanizmov. Ne glede na to, pojav take globalne zgradbe v omrežju prinaša nekatera pomembna vprašanja, povezana z (psihološkim) razvojem otrok, na katera je mogoče odgovoriti z upoštevanjem globalne zgradbe omrežja ter lastnosti otrok. Hierarhični bločni model z nekohezivno zadnjo skupino lahko nastane kot rezultat mehanizmov, povezanih s stroški, in mehanizmov, povezanih z vrednostjo. V tem primeru se stroški in vrednost navezujejo na dojemanje alterjevega znanja s strani ega (Nebus, 2006). Zmožnost generiranja globalnih omrežnih zgradb znotraj tega družbenega konteksta, z upoštevanjem lokalnih omrežnih mehanizmov, ki ne upoštevajo lastnosti vozlišč (z izjemo staža), nakazujejo na to, da je mogoče oblikovati take politike podjetja, ki spodbujajo nastanek želenega vzorca pretoka znanja (če tak želen vzorec pretoka znanja v podjetju obstaja). Osrednji prispevek disertacije je spoznanje, da lahko najbolj znane vrste bločnih modelov nastanejo kot rezultat zelo osnovnih lokalnih omrežnih mehanizmov, brez upoštevanja lastnosti vozlišč. Pri analizi razvoja bločnih modelov v empiričnih omrežjih je nujno upoštevati družbeni kontekst nastanka empiričnih omrežij ter vpliv družbenega konteksta na posameznikovo vedenje (Doreian in Conti, 2012).Social scientists often seek to understand the relationship between micro social mechanisms and macro social output. In the context of social networks, different micro social mechanisms are usually operationalized by local network mechanisms, while macro social outputs are operationalized by global network structures (Stadtfeld, 2018). Therefore, the aim of this dissertation is to study the relationship between local network mechanisms and global network structures. Not only is the emergence of the selected global network structures addressed, but so too is the transition from one global network structure to another. A blockmodel is used to define a global network structure. A blockmodel is defined as a network in which the nodes represent clusters of equivalent nodes (according to the structure of their links) from the studied network, while the links in a blockmodel represent the relationships between and within the clusters. The term “block” refers to a submatrix in an adjacency matrix that shows the relationships between nodes from two different clusters or between nodes from the same cluster (Doreian, Batagelj, & Ferligoj, 2005). Moreover, the social (network) mechanisms can be defined in different ways. Common to the various definitions is the claim that social mechanisms hold an important explanatory role (Hedström & Swedberg, 1998). Stadtfeld (2018) and Hedström & Swedberg (1998) defined three types of mechanisms: situational mechanisms (related to the global network structure’s impact on, e.g. the beliefs, desires and opportunities of an individual), action-formation mechanisms (associated with the impact of individuals’ beliefs, desires and opportunities on their actions/behaviour) and transformational mechanisms (related to the impact of individuals’ actions on the global network structure). In this study, the main focus is given to the last two types of local network mechanisms. The dissertation consists of two parts. The ability to generate networks with the selected blockmodel types, by considering only the triad types, is addressed in the first part. This research question is especially important because there is no known systematic study addressing a relationship between different triad types and blockmodels as the operationalization of global network structures. Whether the selected blockmodel types can be generated by considering only the triad types without any nodes’ attributes shows that these blockmodels can emerge as a consequence of local network mechanisms such as popularity, assortativity and others. To study the mentioned research question, different triad types are classified in the set of allowed and the set of forbidden triad types for each blockmodel type that is considered. A given triad type is called ‘allowed’ if its frequency in a given ideal blockmodel is higher than 0otherwise, it is called ‘forbidden’. The proposed Relocating Links algorithm (RL algorithm) and the Markov Chain Monte Carlo algorithm (MCMC algorithm) are used to generate networks. In general, most studied blockmodels can be generated by only considering different triad types. This shows that some global network structures can emerge by virtue of the local network mechanisms that does not include the nodes’ attributes. The second part of the dissertation considers local network mechanisms, instead of local network structures, in the context of different blockmodel types. The local network mechanisms are processes that drive the specific actions of the nodes in the network, as described above. Different local network mechanisms are operationalized using different network statistics, which are considered by the nodes, when they obtain an opportunity to change the status of their links. This is done by different proposed algorithms from the NEM family. Given that there are many possible blockmodel types and possible local network mechanisms, the social context of the study is taken into account to select the most relevant blockmodel types and corresponding local network mechanisms. Two such social contexts considered in this dissertation are: (i) friendships and likings among pre-schoolersand (ii) the flow of knowledge among employees of an international, knowledge-based company. Based on these two social contexts, two blockmodel types are proposed: an (symmetric and asymmetric) core-cohesive blockmodel, and a hierarchical-cohesive blockmodel with last non-cohesive group. It is shown that the symmetric core-cohesive blockmodel type and the hierarchical-cohesive blockmodel with the last non-cohesive group are appropriate to be considered in the social context relating to a kindergarten and a company. The results of the Monte Carlo simulations show that the symmetric and asymmetric core-cohesive blockmodel types can emerge due to the mutuality, popularity, assortativity (of in-degree) and transitivity-related local network mechanisms when the initial global network structure is an empty network, a network with a cohesive blockmodel, or a network with an asymmetric core-periphery blockmodel. It was also shown (based on empirical data collected within a larger longitudinal study in the USA) that the symmetric core-cohesive blockmodel type appears in interactional networks among pre-schoolers. The fact this blockmodel type can be generated by the selected local network mechanisms does not imply that the global network structures of the empirical networks emerged due to the studied local network mechanisms. However, the appearance of this blockmodel type in the empirical data raises some very important developmental questions, which should be answered by considering the nodes’ attributes. A hierarchical-cohesive blockmodel with the last non-cohesive group can emerge as a result of so-called value-related mechanisms and cost-related mechanisms. Value and cost are defined through the ego\u27s perception of the costs of obtaining the alter\u27s knowledge and the value of the knowledge so obtained (Nebus, 2006). The ability to generate the global network structure, with local network mechanisms that do not consider the nodes’ attributes (except tenure), indicates that a company can develop policies that lead a knowledge flow towards the desired global structure (if it has one). The most important contribution of this dissertation is the observation that the most common blockmodel types can be generated by the basic local network mechanisms, without taking the attributes of the nodes into account. However, it is necessary to consider the social context and corresponding constraints on the nodes’ characteristics and their behaviour (Doreian & Conti, 2012) while analysing evolution of the global network in real networks

Stability of co-authorship blockmodels

Sodelovanje v znanosti igra pomembno vlogo tako v produkciji, kot v deseminaciji znanstvenega védenja. Čeprav so njegove meje težko določljive, je pogosto operacionalizirano skozi so-avtorstva znanstvenih bibliografskih enot, ki predstavljajo enega poglavitnih formalnih rezultatov znanstvenega sodelovanja. Iz osebnih bibliografij raziskovalcev je mogoče ustvariti tako imenovana so-avtorska omrežja, ki omogočajo preučevanje povezanosti nekaterih značilnosti raziskovalcev z vzorci vzpostavljanja so-avtorskih povezav, na ravni celotnega omrežja pa tudi ugotavljanje strukture tovrstnih omrežij. Z analizo so-avtorskih omrežij štirih znanstvenih disciplin v štirih petletnih obdobjih so Kronegger et al. (2011) z bločnim modeliranjem potrdili domnevo o strukturi tipa več-centrov—semi-periferija—periferija. Pričujoče delo analizo razširja na skoraj vse znanstvene discipline, kot jih opredeljuje Javna agencija za raziskovalno dejavnost Republike Slovenije (ARRS) in poleg strukture sodelovanja v znanosti naslovi še vprašanje stabilnosti znanstvenih sodelovanj skupin raziskovalcev glede na pripadnost vedi. Struktura so-avtorskih omrežij slovenskih raziskovalcev je preverjena z metodo neposrednega pred-določenega bločnega modeliranja, za merjenje stabilnosti dobljenih skupin raziskovalcev v času pa so vpeljane različne prilagoditve popravljenega Randovega indeksa. V kontekstu preučevanja so-avtorskih omrežij v dveh časovnih obdobjih, 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. Prilagojeni Randovi indeksi omogočajo primerjanje podobnosti dveh razvrstitev, ki sta izračunani na dveh množicah enot, kjer je ena množica enot podmnožica druge množice enot, združevanje in deljenje skupin v času pa različno vplivata na vrednost predstavljenih koeficientov. Predpostavljena struktura omrežja več-centrov—semi-periferija—periferija je značilna za vse analizirane discipline. Povprečna velikost dobljenih centrov je statistično značilno (p < 0,05) večja v prvem obdobju (5,6 raziskovalcev), v primerjavi z drugim obdobjem (4,4 raziskovalci). Glede na področje raziskovanja pa je povprečna velikost centrov statistično značilno (p < 0,05) višja v naravoslovno-tehniških disciplinah (4,6 raziskovalcev), kakor v družboslovno-humanističnih disciplinah (3,8 raziskovalcev). Stabilnost skupin raziskovalcev na ravni disciplin je relativno nizka in je prej posledica mnogih kratkoročnih sodelovanj, kakor prisotnosti deljenja raziskovalnih skupin. Na ravni ved je povprečna stabilnost disciplin statistično značilno večja v vedah Tehnika in Medicina v primerjavi s Humanistiko, medtem ko med združenimi vedami v skupini naravoslovno-tehniških ved in družboslovno-humanističnih ved ni razlike v povprečni stabilnosti dobljenih centrov.Collaboration in science plays an important role in the production as in the dissemination of a new scientific knowledge. Even there is hard to define 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)