The Problem of Action at a Distance in Networks and the Emergence of Preferential Attachment from Triadic Closure

In this paper, we characterise the notion of preferential attachment in networks as action at a distance, and argue that it can only be an emergent phenomenon -- the actual mechanism by which networks grow always being the closing of triangles. After a review of the concepts of triangle closing and preferential attachment, we present our argument, as well as a simplified model in which preferential attachment can be derived mathematically from triangle closing. Additionally, we perform experiments on synthetic graphs to demonstrate the emergence of preferential attachment in graph growth models based only on triangle closing.Comment: 13 pages, three figure

Gender Disparities in Science? Dropout, Productivity, Collaborations and Success of Male and Female Computer Scientists

Scientific collaborations shape ideas as well as innovations and are both the substrate for, and the outcome of, academic careers. Recent studies show that gender inequality is still present in many scientific practices ranging from hiring to peer-review processes and grant applications. In this work, we investigate gender-specific differences in collaboration patterns of more than one million computer scientists over the course of 47 years. We explore how these patterns change over years and career ages and how they impact scientific success. Our results highlight that successful male and female scientists reveal the same collaboration patterns: compared to scientists in the same career age, they tend to collaborate with more colleagues than other scientists, seek innovations as brokers and establish longer-lasting and more repetitive collaborations. However, women are on average less likely to adapt the collaboration patterns that are related with success, more likely to embed into ego networks devoid of structural holes, and they exhibit stronger gender homophily as well as a consistently higher dropout rate than men in all career ages

On the inadequacy of nominal assortativity for assessing homophily in networks

Nominal assortativity (or discrete assortativity) is widely used to characterize group mixing patterns and homophily in networks, enabling researchers to analyze how groups interact with one another. Here we demonstrate that the measure presents severe shortcomings when applied to networks with unequal group sizes and asymmetric mixing. We characterize these shortcomings analytically and use synthetic and empirical networks to show that nominal assortativity fails to account for group imbalance and asymmetric group interactions, thereby producing an inaccurate characterization of mixing patterns. We propose adjusted nominal assortativity and show that this adjustment recovers the expected assortativity in networks with various level of mixing. Furthermore, we propose an analytical method to assess asymmetric mixing by estimating the tendency of inter- and intra-group connectivities. Finally, we discuss how this approach enables uncovering hidden mixing patterns in real-world networks.Comment: 19 pages, 3 figure

Mapping bilateral information interests using the activity of Wikipedia editors

We live in a global village where electronic communication has eliminated the geographical barriers of information exchange. The road is now open to worldwide convergence of information interests, shared values, and understanding. Nevertheless, interests still vary between countries around the world. This raises important questions about what today's world map of in- formation interests actually looks like and what factors cause the barriers of information exchange between countries. To quantitatively construct a world map of information interests, we devise a scalable statistical model that identifies countries with similar information interests and measures the countries' bilateral similarities. From the similarities we connect countries in a global network and find that countries can be mapped into 18 clusters with similar information interests. Through regression we find that language and religion best explain the strength of the bilateral ties and formation of clusters. Our findings provide a quantitative basis for further studies to better understand the complex interplay between shared interests and conflict on a global scale. The methodology can also be extended to track changes over time and capture important trends in global information exchange.Comment: 11 pages, 3 figures in Palgrave Communications 1 (2015

Analyzing the network structure and gender differences among the members of the Networked Knowledge Organization Systems (NKOS) community

In this paper, we analyze a major part of the research output of the Networked Knowledge Organization Systems (NKOS) community in the period 2000-2016 from a network analytical perspective. We focus on the papers presented at the European and US NKOS workshops and in addition four special issues on NKOS in the last 16 years. For this purpose, we have generated an open dataset, the "NKOS bibliography" which covers the bibliographic information of the research output. We analyze the co-authorship network of this community which results in 123 papers with a sum of 256 distinct authors. We use standard network analytic measures such as degree, betweenness and closeness centrality to describe the co-authorship network of the NKOS dataset. First, we investigate global properties of the network over time. Second, we analyze the centrality of the authors in the NKOS network. Lastly, we investigate gender differences in collaboration behavior in this community. Our results show that apart from differences in centrality measures of the scholars, they have higher tendency to collaborate with those in the same institution or the same geographic proximity. We also find that homophily is higher among women in this community. Apart from small differences in closeness and clustering among men and women, we do not find any significant dissimilarities with respect to other centralities

Investigating the Relationship between Perceived Organizational Support and Organizational Trust

The present research aims to determine relationship between perceived organizational support and organizational trust. It was a descriptive correlation study. The statistical population of the research included all female teachers of high schools of district 4 of Isfahan City. Organizational support questionnaire developed by Eisenberger et al. (1986) and Sashkin's organizational trust questionnaire (1988) were instruments used in this research. 1986questionnaire. For organizational trust questionnaire, alpha was equal to 0.90 and for perceived organizational support, it was equal to 0.83. The results showed that there is a significant relationship between perceived organizational support and organizational trust. Furthermore, the results showed that there are significant relationships between perceived organizational support and 10 dimensions of organizational trust except for manager’s honesty for predicting future results

Unveiling homophily beyond the pool of opportunities

Unveiling individuals' preferences for connecting with similar others (choice homophily) beyond the structural factors determining the pool of opportunities, is a challenging task. Here, we introduce a robust methodology for quantifying and inferring choice homophily in a variety of social networks. Our approach employs statistical network ensembles to estimate and standardize homophily measurements. We control for group size imbalances and activity disparities by counting the number of possible network configurations with a given number of inter-group links using combinatorics. This method provides a principled measure of connection preferences and their confidence intervals. Our framework is versatile, suitable for undirected and directed networks, and applicable in scenarios involving multiple groups. To validate our inference method, we test it on synthetic networks and show that it outperforms traditional metrics. Our approach accurately captures the generative homophily used to build the networks, even when we include additional tie-formation mechanisms, such as preferential attachment and triadic closure. Results show that while triadic closure has some influence on the inference, its impact is small in homophilic networks. On the other hand, preferential attachment does not perturb the results of the inference method. We apply our method to real-world networks, demonstrating its effectiveness in unveiling underlying gender homophily. Our method aligns with traditional metrics in networks with balanced populations, but we obtain different results when the group sizes or degrees are imbalanced. This finding highlights the importance of considering structural factors when measuring choice homophily in social networks

First-mover advantage explains gender disparities in physics citations

Mounting evidence suggests that publications and citations of scholars in the STEM fields (Science, Technology, Engineering and Mathematics) suffer from gender biases. In this paper, we study the physics community, a core STEM field in which women are still largely underrepresented and where these gender disparities persist. To reveal such inequalities, we compare the citations received by papers led by men and women that cover the same topics in a comparable way. To do that, we devise a robust statistical measure of similarity between publications that enables us to detect pairs of similar papers. Our findings indicate that although papers written by women tend to have lower visibility in the citation network, pairs of similar papers written by men and women receive comparable attention when corrected for the time of publication. These analyses suggest that gender disparity is closely related to the first-mover and cumulative advantage that men have in physics, and is not an intentional act of discrimination towards women.Comment: 21 pages, 8 tables, 10 figure

Collective Attention towards Scientists and Research Topics

Emergent patterns of collective attention towards scientists and their research may function as a proxy for scientific impact which traditionally is assessed via committees that award prizes to scientists. Therefore it is crucial to understand the relationships between scientific impact and online demand and supply for information about scientists and their work. In this paper, we compare the temporal pattern of information supply (article creations) and information demand (article views) on Wikipedia for two groups of scientists: scientists who received one of the most prestigious awards in their field and influential scientists from the same field who did not receive an award. Our research highlights that awards function as external shocks which increase supply and demand for information about scientists, but hardly affect information supply and demand for their research topics. Further, we find interesting differences in the temporal ordering of information supply between the two groups: (i) award-winners have a higher probability that interest in them precedes interest in their work; (ii) for award winners interest in articles about them and their work is temporally more clustered than for non-awarded scientists.Comment: Accepted at the 2018 ACM on Web Science Conference, Amsterdam, Netherlands, May 27-30, 201