Disconnected, fragmented, or united? A trans-disciplinary review of network science

During decades the study of networks has been divided between the efforts of social scientists and natural scientists, two groups of scholars who often do not see eye to eye. In this review I present an effort to mutually translate the work conducted by scholars from both of these academic fronts hoping to continue to unify what has become a diverging body of literature. I argue that social and natural scientists fail to see eye to eye because they have diverging academic goals. Social scientists focus on explaining how context specific social and economic mechanisms drive the structure of networks and on how networks shape social and economic outcomes. By contrast, natural scientists focus primarily on modeling network characteristics that are independent of context, since their focus is to identify universal characteristics of systems instead of context specific mechanisms. In the following pages I discuss the differences between both of these literatures by summarizing the parallel theories advanced to explain link formation and the applications used by scholars in each field to justify their approach to network science. I conclude by providing an outlook on how these literatures can be further unified

Community structure in co-inventor networks affects time to first citation for patents

We have investigated community structure in the co-inventor network of a given cohort of patents and related this structure to the dynamics of how these patents acquire their first citation. A statistically significant difference in the time lag until first citation is linked to whether or not this citation comes from a patent whose listed inventors share membership in the same communities as the inventors of the cited patent. Although the inventor-community structures identified by different community-detection algorithms differ in several aspects, including the community-size distribution, the magnitude of the difference in time to first citation is robustly exhibited. Our work is able to quantify the expected acceleration of knowledge flow within inventor communities and thereby further establishes the utility of network-analysis tools for studying innovation dynamics.Comment: 16 pages, 4 figures, BioMedCentral article style, to appear in Applied Network Science - special issue 'Community structure in networks

How to measure influence in social networks?

Today, social networks are a valued resource of social data that can be used to understand the interactions among people and communities. People can influence or be influenced by interactions, shared opinions and emotions. How-ever, in the social network analysis, one of the main problems is to find the most influential people. This work aims to report on the results of literature review whose goal was to identify and analyse the metrics, algorithms and models used to measure the user influence on social networks. The search was carried out in three databases: Scopus, IEEEXplore, and ScienceDirect. We restricted pub-lished articles between the years 2014 until 2020, in English, and we used the following keywords: social networks analysis, influence, metrics, measurements, and algorithms. Backward process was applied to complement the search consid-ering inclusion and exclusion criteria. As a result of this process, we obtained 25 articles: 12 in the initial search and 13 in the backward process. The literature review resulted in the collection of 21 influence metrics, 4 influence algorithms, and 8 models of influence analysis. We start by defining influence and presenting its properties and applications. We then proceed by describing, analysing and categorizing all that were found metrics, algorithms, and models to measure in-fluence in social networks. Finally, we present a discussion on these metrics, al-gorithms, and models. This work helps researchers to quickly gain a broad per-spective on metrics, algorithms, and models for influence in social networks and their relative potentialities and limitations.This work has been supported by IViSSEM: POCI-01-0145-FEDER-28284, COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020

Sistemas migratorios latinoamericanos y desarrollo humano : el alcance de usar el análisis de redes sociales

Los sistemas migratorios se han estudiado desde una perspectiva demográfica que involucra medidas clásicas de propensiones a migrar teniendo en cuenta los efectos en dos puntos particulares de origen y destino, brindando información sobre las características principales de la elección de una región específica compuesta por países. Para los sistemas migratorios, el Análisis de Redes Sociales (ARS) proporciona una herramienta para estudiar las relaciones entre países, la importancia de cada país dentro de la red y la influencia de las variables del país en los patrones generales de una red específica. El presente artículo analiza los acumulados de migrantes proporcionados por las Naciones Unidas para observar la red acumulada más reciente. Este artículo pretende responder a dos preguntas concretas: i) ¿Cuáles son los principales países que intervienen en la red latinoamericana? ii) Si se realiza una descomposición de las variables del Índice de Desarrollo Humano (IDH) ¿Qué variables de éstas pueden afectar los patrones generales de migración? Los resultados muestran una gran influencia de la hiperconectividad de las redes, cuestión que resulta problemática a la hora de plantear modelos sobre la distribución de las migraciones en la red.Migration systems have been studied from a demographic perspective that involves classical measures of the propensities to migrate and taking into account the effects at the points of origin and destination, providing information on the main characteristics of the specific choice of countries. For the migratory systems, the Social Network Analysis (SNA), the tool to study, the relations between the countries, the importance of each country within the network and the influence of the variables of the country in the general distribution of migrants through random exponential graph models (ERGM). This article analyzes the populations of migrants provided by the United Nations. This article aims to answer two specific questions: i) What are the principles of the countries that intervene in the Latin American network? ii) If a decomposition is made by Human Development Index (HDI) variables, what variables of them can affect the general patterns of migration? The results show a great influence of the hyperconnectivity of the networks, the issue that is problematic at the time of the plant, the models on the distribution of migrations in the network

Teaching public administrators and leaders to handle complexity

Understanding and working under complexity has become ‘the new normal’ in public administration. Hence complexity must also be integrated into teaching and training of public administrators, not only in higher education but also in in-service training and educating wider society. This can be done by combining the ongoing research agenda into courses and teaching methods. This article describes the integration of complexity thinking and teaching in one university, both by giving examples on the courses and methods applied, student feedback received and by anticipating future developments. Finally, practical advice for teachers of complexity is given