scholarly journals De la hermenéutica a las redes de datos: Extracción de datos y visualización de redes en fuentes históricas

2017 ◽  
Author(s):  
Marten Düring
Keyword(s):  
Social Network ◽  
Data Analysis ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Qualitative Data ◽  
Redes Sociales ◽  
Qualitative Data Analysis

La visualizaciones de redes pueden ayudar a los humanistas a revelar patrones complejos escondidos y estructuras en fuentes textuales. Este tutorial explica cómo extraer datos en red (personas, instituciones, lugares, etcétera.) de fuentes históricas a través del uso de métodos no especializados desarrollados en el marco del análisis de datos qualitativos (Qualitative Data Analysis, QDA) y el análisis de redes sociales (Social Network Analysis, SNA), y cómo visualizar estos datos con Palladio, una aplicación independiente de plataforma y que es particularmente fácil de usar.

scholarly journals From Hermeneutics to Data to Networks: Data Extraction and Network Visualization of Historical Sources

2015 ◽  
Author(s):  
Marten Düring
Keyword(s):  
Social Network ◽  
Data Analysis ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Qualitative Data ◽  
Data Extraction ◽  
Network Visualization ◽  
Network Data ◽  
Qualitative Data Analysis ◽  
Historical Sources

Network visualizations can help humanities scholars reveal hidden and complex patterns and structures in textual sources. This tutorial explains how to extract network data (people, institutions, places, etc) from historical sources through the use of non-technical methods developed in Qualitative Data Analysis (QDA) and Social Network Analysis (SNA), and how to visualize this data with the platform-independent and particularly easy-to-use Palladio.

Social Network Analysis

2020 ◽  
pp. 107-117
Author(s):  
Sheik Abdullah A. ◽  
Abiramie Shree T. G. R.
Keyword(s):  
Social Network ◽  
Data Analysis ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Data Storage ◽  
Social Data ◽  
Cloud Data ◽  
Huge Data ◽  
Cloud Data Storage ◽  
Social Data Analysis

Each day, 2.5 quintillion bytes of data are generated due to our daily activity. It is due to the vast amount of use of the smart mobiles, Cloud data storage, and the Internet of Things. In earlier days, these technologies were utilized by large IT companies and the private sector, but now each person has a high-end smartphone along with the cloud and IoT for the easy storage of data and backup. The analysis of the data generated by social media is a tedious process and involves a lot of techniques. Some tools for social network analysis are: Gephi, Networkx, IGraph, Pajek, Node XL, and cytoscope. Apart from these tools there are various efficient social data analysis algorithms that are far more helpful in doing analytics. The need for and use of social network analysis is very helpful in our current problem of huge data generation. In this chapter, the need for the analysis of social data along with the tools that are needed for the analysis and the techniques that are to be implemented in the field of social data analysis are covered.

scholarly journals Advancing clinical leadership to improve the implementation of evidence-based practice in surgery: a longitudinal mixed-method study protocol

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Amy Grove ◽  
Aileen Clarke ◽  
Graeme Currie ◽  
Andy Metcalfe ◽  
Catherine Pope ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Mixed Method ◽  
Qualitative Data ◽  
Mixed Method Study ◽  
Evidence Based ◽  
Theory Approach ◽  
Cross Sectional ◽  
Clinical Leadership

Abstract Background Clinical leadership is fundamental in facilitating service improvements in healthcare. Few studies have attempted to understand or model the different approaches to leadership which are used when promoting the uptake and implementation of evidence-based interventions. This research aims to uncover and explain how distributed clinical leadership can be developed and improved to enhance the use of evidence in practice. In doing so, this study examines implementation leadership in orthopaedic surgery to explain leadership as a collective endeavour which cannot be separated from the organisational context. Methods A mixed-method study consisting of longitudinal and cross-sectional interviews and an embedded social network analysis will be performed in six NHS hospitals. A social network analysis will be undertaken in each hospital to uncover the organisational networks, the focal leadership actors and information flows in each organisation. This will be followed by a series of repeated semi-structured interviews, conducted over 4 years, with orthopaedic surgeons and their professional networks. These longitudinal interviews will be supplemented by cross-sectional interviews with the national established surgical leaders. All qualitative data will be analysed using a constructivist grounded theory approach and integrated with the quantitative data. The participant narratives will enrich the social network to uncover the leadership configurations which exist, and how different configurations of leadership are functioning in practice to influence implementation processes and outcomes. Discussion The study findings will facilitate understanding about how and why different configurations of leadership develop and under what organisational conditions and circumstances they are able to flourish. The study will guide the development of leadership interventions that are grounded in the data and aimed at advancing leadership for service improvement in orthopaedics. The strength of the study lies in the combination of multi-component, multi-site, multi-agent methods to examine leadership processes in surgery. The findings may be limited by the practical challenges of longitudinal qualitative data collection, such as ensuring participant retention, which need to be balanced against the theoretical and empirical insights generated through this comprehensive exploration of leadership across and within a range of healthcare organisations.

scholarly journals Inter-player variability in game patterns in high-level women's volleyball: A study with Outside Hitters (Near vs. Away) using Social Network Analysis. [Variabilidad entre jugadores en los patrones de juego en el voleibol femenino de alto nivel: Un estudio con bateadores externos (Cerca versus Lejos) usando Análisis de Redes Sociales].

2021 ◽  
Vol 17 (65) ◽  
pp. 234-250
Author(s):  
João Bernardo Martins ◽  
◽  
Isabel Mesquita ◽  
Ademilson Mendes ◽  
Letícia Santos ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Team Sports ◽  
Eigenvector Centrality ◽  
Redes Sociales ◽  
Functional Roles ◽  
High Level ◽  
Women's Volleyball ◽  
After Error

A wide body of research on team sports has focused on positional status based differences, providing information on inter-player variability according to the functional roles within the game. However, research addressing inter-player variability within the same positional/function status is scarce. The present article presents an analysis of inter-player variability within the same positional status during critical moments, in high-level women's volleyball, using Social Network Analysis. Attack actions of the outside hitters near (OHN) and away (OHA) from the setter were analysed in ten matches from the 2019 Volleyball Nations League Finals (268 plays). Two independent Eigenvector Centrality networks were created, one for OHN and another for OHA. Main results: (a) in side-out with ideal setting conditions, the OHA used more tips and exploration of the block than the OHN; under non-ideal setting conditions, the OHN had slower attack tempos than the OHA; (b) OHA used tip and directed attacks after error situations while OHN was typically not requested after error situations; (c) in transition, OHN typically attacked after having performed a previous action, performing a dual task within each ball possession, while OHA only attacked when there was no prior action; (d) there were also inter-positional similarities, with both OHN and OHA preferring a strong attack in ideal conditions during KI and KIV, and slower tempos in transition in non-ideal conditions. Conclusions: Even within the same positional status, there seems to be subtle, but relevant inter-player variability. Consequently, coaches should devote careful attention when assigning players to positional.

Mapping movements: a call for qualitative social network analysis

2020 ◽  
pp. 146879412092767
Author(s):  
India Luxton ◽  
Joshua Sbicca
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Life ◽  
Qualitative Data ◽  
Centrality Measures ◽  
Organization Level ◽  
Starting Point ◽  
Food Movement ◽  
Interpretive Process

Social network analysis (SNA) is an interdisciplinary method that takes as its starting point the premise that social life is created primarily and most importantly by relations and the patterns formed by these relations. While SNA is often associated with the quantitative analysis of network measures, we illustrate through our overall mapping of, and interpretation of the relations within the Denver food movement, the advantages of a qualitative approach. We bring together information from surveys, network diagrams, betweenness centrality measures, and interviews to offer an interpretive process that reveals both the structure and activist- and organization-level meanings to explain resource mobilization and collaboration. We propose that qualitative SNA allows researchers to (a) understand the context and content of network structures and (b) better interpret quantitative measures with additional qualitative data. Based on our findings, we additionally suggest that for social movement scholars, qualitative SNA offers a deeper understanding of how organizations collaborate to advance organizational and movement goals.

scholarly journals Un estudio socio-métrico del tema de la moral económica y de su proyección en la Escuela de Salamanca, 1526-1670 / A Sociometric Study on the Topic of Moral Economy and its Projection in the School of Salamanca, 1526-1670

2017 ◽  
pp. 55
Author(s):  
Osvaldo Víctor Pereyra
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Moral Economy ◽  
Redes Sociales ◽  
School Of Salamanca ◽  
The Cross

This article propounds a network analysis of the group of scholastic theologians that stood out in the sixteenth and seventeenth centuries because of their examination of topics of moral economy, better known as the School of Salamanca. To this purpose we suggest the study of their dynamic through three themes: their junction of routes, the diversity of trajectories and the cross-citations among their members. The objective of this analysis is to visualize the importance and relevance of the so-called methods of Social Network Analysis (SNA) in historical field.Key WordsNetworks, Salamanca theologians, centrality, mediation, School of Salamanca.ResumenEl presente artículo presenta un análisis de carácter reticular del grupo de los teólogos escolásticos que sobresalieron en los siglos XVI y XVII por su examen de problemas de moral económica, más conocido como la Escuela de Salamanca. Para tal objeto proponemos el estudio de su dinámica a partir de tres ejes: su confluencia de recorridos, su diversidad de trayectorias y las citas cruzadas entre sus miembros. El propósito del dicho análisis es mostrar la importancia y pertinencia de los llamados Análisis de Redes Sociales (ARS) en el estudio histórico.Palabras clavesRedes, teólogos salmanticenses, centralidad, intermediación, Escuela de Salamanca.

scholarly journals Big Data Analysis of the Key Attributes Related to Stress and Mental Health in Korean Taekwondo Student Athletes

2022 ◽  
Vol 14 (1) ◽  
pp. 477
Author(s):  
Sung-Un Park ◽  
Jung-Woo Jeon ◽  
Hyunkyun Ahn ◽  
Yoon-Kwon Yang ◽  
Wi-Young So
Keyword(s):  
Mental Health ◽  
Big Data ◽  
Social Network ◽  
Data Analysis ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Correlation Analysis ◽  
Student Athletes ◽  
Big Data Analysis ◽  
Degree Centrality

In the present study, we used big data analysis to examine the key attributes related to stress and mental health among Korean Taekwondo student-athletes. Keywords included “Taekwondo + Student athlete + Stress + Mental health”. Naver and Google databases were searched to identify research published between 1 January 2010 and 31 December 2019. Text-mining analysis was performed on unstructured texts using TEXTOM 4.5, with social network analysis performed using UCINET 6. In total, 3149 large databases (1.346 MB) were analyzed. Two types of text-mining analyses were performed, namely, frequency analysis and term frequency-inverse document frequency analysis. For the social network analysis, the degree centrality and convergence of iterated correlation analysis were used to deduce the node-linking degree in the network and to identify clusters. The top 10 most frequently used terms were “stress”, “Taekwondo”, “health”, “player”, “student”, “mental”, “exercise”, “mental health”, “relieve”, and “child.” The top 10 most frequently occurring results of the TF-IDF analysis were “Taekwondo”, “health”, “player”, “exercise”, “student”, “mental”, “stress”, “mental health”, “child” and “relieve”. The degree centrality analysis yielded similar results regarding the top 10 terms. The convergence of iterated correlation analysis identified six clusters: student, start of dream, diet, physical and mental, sports activity, and adult Taekwondo center. Our results emphasize the importance of designing interventions that attenuate stress and improve mental health among Korean Taekwondo student-athletes.

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