scholarly journals Women and universities in El País (1977-2011): A methodological proposal for use of the ITCS for historical analysis

2019 ◽  
Vol 8 (1) ◽  
pp. 009
Author(s):  
Carlos G. Figuerola ◽  
Tamar Groves ◽  
Francisco J. Rodríguez
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Text Mining ◽  
Historical Analysis ◽  
Historical Research ◽  
Software Systems ◽  
Practical Case ◽  
Computer Tools ◽  
Analysis Techniques

The practice of historical research in recent years has been substantially affected by the emergence of the so-called digital humanities. New computer tools have been appearing, software systems capable of processing vast quantities of information in ways that until recently were inconceivable. Text mining and social network analysis techniques are sophisticated instruments that can help render a more enriching reading of the available data and draw useful conclusions. We reflect on this in the first part of this article, and then apply these tools to a practical case: quantifying and identifying the women who appear in university-related articles in the newspaper El País from its founding until 2011.

scholarly journals Research on China’s Green Finance Policies Based on Text Mining

2020 ◽  
Vol 185 ◽  
pp. 02024
Author(s):  
Yuqing Liao ◽  
Jingliang Chen
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
High Frequency ◽  
Policy Documents ◽  
Analysis Techniques ◽  
The Past ◽  
Word Cloud ◽  
Green Finance ◽  
Occurrence Matrix

Based on the green finance policies in China from 2017 to 2019, this paper extracts feature and high-frequency words from policy documents, uses word cloud diagram, co-occurrence matrix and social network analysis techniques to quantitatively analyse the information contained in the green finance policies over the past three years and highlights the hot issues in question, thus providing a multi-layered and wideranging pathway for facilitating the orderly development of green finance industries across China.

scholarly journals Carlos Pastore y el Instituto Histórico y Geográfico del Uruguay: redes intelectuales y homenajes en el Centenario de Artigas

2021 ◽  
pp. 353-387
Author(s):  
Matías Borba Eguren
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Text Mining ◽  
La Red

El presente trabajo analiza la participación de Carlos Pastore – intelectual y político paraguayo, exiliado en Montevideo en 1942 – en los homenajes a Artigas, realizados por el Instituto Histórico y Geográfico del Uruguay en 1950. Se busca establecer su papel como articulador entre el Instituto y otros paraguayos – en su mayoría exiliados –, aplicando técnicas del social network analysis y de text mining, para graficar la red político-historiográfica a su alrededor. Se pretende señalar cómo los homenajes a Artigas fueron una oportunidad para los exiliados paraguayos de utilizar el pasado como herramienta de militancia contra la situación política de Paraguay.

scholarly journals SOCIAL NETWORK ANALYSIS FOR CHURN PREDICTION IN TELECOM DATA

2016 ◽  
pp. 295-302
Author(s):  
PUSHPA PUSHPA ◽  
Dr. Shobha G
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social World ◽  
Centrality Measures ◽  
Churn Prediction ◽  
Huge Amount ◽  
Analysis Techniques ◽  
Manual Analysis ◽  
The Social

Social Network Analysis (SNA) is a set of research procedures for identifying group of people who share common structures in systems based on the relations among actors. Grounded in graph and system theories, this approach has proven to be powerful measures for studying networks in various industries like Telecommunication, banking, physics and social world, including on the web. Since Telecommunication industries deals with huge amount of data, manual analysis of data is very difficult. In this paper we explore the Social Network Analysis techniques for Churn Prediction in Telecom data. Typical work on social network analysis includes the construction of multi-relational telecom social network and centrality measures for prediction of churners in telecom social network.

An Investigation of Competitor Networks in Manufacturing Strategy and Implications for Performance

2018 ◽  
pp. 850-879
Author(s):  
Eve D. Rosenzweig ◽  
Elliot Bendoly
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Market Performance ◽  
Manufacturing Strategy ◽  
Strategy Research ◽  
Analysis Techniques ◽  
The Relationship ◽  
Moderating Role

Our study demonstrates the value of taking a more encompassing and explicit view of competition in manufacturing strategy research. In doing so, we go beyond a dyadic-based approach and investigate the ways in which the degree of competition among firms in a network influences performance. Using social network analysis techniques, we develop a novel measure—which we refer to as competitor infighting—that captures the extent to which a firm's rivals compete amongst themselves. Our results suggest that a firm has a greater, unimpeded opportunity to demonstrate market gains as the degree of competition among its rivals increases, all else equal. In fact, competitor infighting is a better predictor of market performance in our sample than is a simpler, though perhaps more traditional, count of competitors. It serves an important moderating role in the relationship between a firm's operational weaknesses and market performance. As predicted, we find that as competitor infighting increases, the relationship between operational weaknesses and market performance is diminished.

An Investigation of Competitor Networks in Manufacturing Strategy and Implications for Performance

2017 ◽  
pp. 43-82
Author(s):  
Eve D. Rosenzweig ◽  
Elliot Bendoly
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Market Performance ◽  
Manufacturing Strategy ◽  
Strategy Research ◽  
Analysis Techniques ◽  
The Relationship ◽  
Moderating Role

Our study demonstrates the value of taking a more encompassing and explicit view of competition in manufacturing strategy research. In doing so, we go beyond a dyadic-based approach and investigate the ways in which the degree of competition among firms in a network influences performance. Using social network analysis techniques, we develop a novel measure—which we refer to as competitor infighting—that captures the extent to which a firm's rivals compete amongst themselves. Our results suggest that a firm has a greater, unimpeded opportunity to demonstrate market gains as the degree of competition among its rivals increases, all else equal. In fact, competitor infighting is a better predictor of market performance in our sample than is a simpler, though perhaps more traditional, count of competitors. It serves an important moderating role in the relationship between a firm's operational weaknesses and market performance. As predicted, we find that as competitor infighting increases, the relationship between operational weaknesses and market performance is diminished.

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