Emmanuel Lazega et Tom A. B. Snidjers (dir.), Multilevel Network Analysis for Social Sciences

Lectures ◽  
2017 ◽  
Author(s):  
Robin Lenoir
Keyword(s):  
Social Sciences ◽  
Network Analysis

scholarly journals What do we see when we look at networks: Visual network analysis, relational ambiguity, and force-directed layouts

2021 ◽  
Vol 8 (1) ◽  
pp. 205395172110184
Author(s):  
Tommaso Venturini ◽  
Mathieu Jacomy ◽  
Pablo Jensen
Keyword(s):  
Social Sciences ◽  
Network Analysis ◽  
Dimensional Space ◽  
Two Dimensional ◽  
Project Networks ◽  
Topological Features ◽  
Exploratory Data ◽  
Inherent Ambiguity ◽  
Visual Network ◽  
Visual Ambiguity

It is increasingly common in natural and social sciences to rely on network visualizations to explore relational datasets and illustrate findings. Such practices have been around long enough to prove that scholars find it useful to project networks in a two-dimensional space and to use their visual qualities as proxies for their topological features. Yet these practices remain based on intuition, and the foundations and limits of this type of exploration are still implicit. To fill this lack of formalization, this paper offers explicit documentation for the kind of visual network analysis encouraged by force-directed layouts. Using the example of a network of Jazz performers, band and record labels extracted from Wikipedia, the paper provides guidelines on how to make networks readable and how to interpret their visual features. It discusses how the inherent ambiguity of network visualizations can be exploited for exploratory data analysis. Acknowledging that vagueness is a feature of many relational datasets in the humanities and social sciences, the paper contends that visual ambiguity, if properly interpreted, can be an asset for the analysis. Finally, we propose two attempts to distinguish the ambiguity inherited from the represented phenomenon from the distortions coming from fitting a multidimensional object in a two-dimensional space. We discuss why these attempts are only partially successful, and we propose further steps towards a metric of spatialization quality.

scholarly journals Hacia la complejidad por la vía de las redes. Nuevas lecciones epistemológicas

2014 ◽  
Author(s):  
Carlos Reynoso
Keyword(s):  
Social Sciences ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Scale Free Network ◽  
New Paradigm ◽  
Scale Free ◽  
Network Research ◽  
Free Network

This paper sur veys the reciprocal impacts between Social Network Analysis and the new paradigm of complexity and chaos theories, as well as the emergence of scale-free network research in the twenty-first centur y. This study is embedded in the context of a histor y of the most momentous events in network theor y and practice , from Euler to Barabási, used as a star ting point to interrogate some critical epistemological issues from the viewpoint of contemporar y social sciences.

scholarly journals Identification of Research Thematic Approaches Based on Keywords Network Analysis in Colombian Social Sciences

Data Mining ◽  
2018 ◽  
Author(s):  
José Hernando Ávila-Toscano ◽  
Ivón Catherine Romero-Pérez ◽  
Ailed Marenco-Escuderos ◽  
Eugenio Saavedra Guajardo
Keyword(s):  
Social Sciences ◽  
Network Analysis

Thick Big Data

2021 ◽  
pp. 210-228
Author(s):  
Dariusz Jemielniak ◽  
Agata Stasik
Keyword(s):  
Social Sciences ◽  
Qualitative Research ◽  
Big Data ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Narrative Analysis ◽  
Digital Data ◽  
Online Research ◽  
Practical Advice

As we witness a radical increase in the volume and variety of digital data, it should not come as a surprise that social sciences have become increasingly ‘datafied’. The traditional social sciences, such as sociology or anthropology, are thus under the threat of becoming marginalized or even irrelevant because of the prevalence of the new methods of research, which require more computational skills. This chapter describes a way for researchers to enter this new domain and keep their advantage of mastering qualitative research relevant: a new, mixed-method of Thick Big Data, relying on a combination of quantitative approaches (data scraping, Social Network Analysis, culturomics, sentiment analysis) with qualitative ones (digital ethnography, narrative analysis, cultural studies). The chapter outlines how these approaches may blend, and offers some practical advice for a researcher without coding skills on how to take the first steps in online research, through examples focused on Wikipedia.

Network analysis in comparative social sciences

2006 ◽  
Vol 42 (3) ◽  
pp. 405-429 ◽  
Author(s):  
Eugenia Roldán Vera ◽  
Thomas Schupp
Keyword(s):  
Social Sciences ◽  
Network Analysis

scholarly journals Network Analysis in the Social Sciences

Science ◽  
2009 ◽  
Vol 323 (5916) ◽  
pp. 892-895 ◽  
Author(s):  
S. P. Borgatti ◽  
A. Mehra ◽  
D. J. Brass ◽  
G. Labianca
Keyword(s):  
Social Sciences ◽  
Network Analysis ◽  
The Social

scholarly journals Network Approach in Health Behavior Research: How Can We Explore New Questions?

2019 ◽  
Author(s):  
Samvel Mkhitaryan ◽  
Rik Crutzen ◽  
Nanne de Vries ◽  
Esther Steenaart
Keyword(s):  
Social Sciences ◽  
Network Analysis ◽  
Health Behavior ◽  
Clinical Psychology ◽  
Network Approach ◽  
Structural Components ◽  
Cross Sectional ◽  
Psychological Variables ◽  
Behavioral Variables ◽  
And Behavior

The network approach has recently been introduced to clinical psychology and provides a powerful framework for analyzing variables in a system. Since then, its applications have rapidly spread to various fields of social sciences. Unlike in the case of clinical psychology, the peculiarities of the phenomena under study in social sciences have not received sufficient attention. In this paper, along with practical illustrations, we discuss what a system of psychological variables represents and what the interrelationships between the variables mean in the context of health behavior research. In addition, we touch upon the structural analysis of the system which hasn’t been the focus of the recent applications of network analysis in health psychology. In this paper, we illustrate two approaches of incorporating observable behavioral variables in a system and strategies for investigating structural components of the system. We illustrate these two approaches with an analysis of cross-sectional data on adolescents’ beliefs and behavior with respect to registering their choice regarding organ donation in the Netherlands. With this paper, we provide researchers with guidance on network analysis of psychological variables. Furthermore, we wish to facilitate a larger discussion on conceptualizing networks of psychological variables, which will guide the analysis and the interpretation of node level interactions as well as network level structures.

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