scholarly journals Implementing Participatory Processes in Forestry Training Using Social Network Analysis Techniques

Forests ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 463 ◽  
Author(s):  
Simone Blanc ◽  
Federico Lingua ◽  
Livio Bioglio ◽  
Ruggero Pensa ◽  
Filippo Brun ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Stakeholder Analysis ◽  
Raw Material ◽  
Strong Interactions ◽  
Analysis Techniques ◽  
Forestry Sector ◽  
Decision Making Processes ◽  
Complex Relationships

Public participation has become an important driver in increasing public acceptance of policy decisions, especially in the forestry sector, where conflicting interests among the actors are frequent. Stakeholder Analysis, complemented by Social Network Analysis techniques, was used to support the participatory process and to understand the complex relationships and the strong interactions among actors. This study identifies the forestry training sector stakeholders in the Western Italian Alps and describes their characteristics and priorities, in relation to training activities on entrepreneurial topics for forestry loggers. The hierarchy among actors has been identified, highlighting their respective roles and influence in decision-making processes. A lack of mutual communication among different and well-separated categories of actors has been identified, while good connections between stakeholders, operating in different territories, despite the presence of administrative and logistical barriers, have been observed. Training is a topic involving actors with different roles and interests. Nevertheless, all actors consider training about how to improve yields of forest operations and how to assess investments, particularly in innovative machinery, to be crucially important and conducive to a better comprehension of the wood supply chain and the enhancement of the raw material.

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 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.

scholarly journals Stakeholder Analysis and Social Network Analysis in the Decision-Making of Industrial Land Redevelopment in China: The Case of Shanghai

2020 ◽  
Vol 17 (24) ◽  
pp. 9206
Author(s):  
Wendong Wu ◽  
Fang He ◽  
Taozhi Zhuang ◽  
Yuan Yi
Keyword(s):  
Decision Making ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Public Space ◽  
Large Scale ◽  
Social Issues ◽  
Stakeholder Analysis ◽  
Industrial Land ◽  
Land Redevelopment

Currently, many large Chinese cities have entered the postindustrial era, leaving a large amount of vacant, inefficiently utilized industrial land and buildings in the inner cities. Industrial land redevelopment (ILR) can benefit cities in multiple ways, such as by increasing urban public space, improving the quality of life of citizens, and improving the environment, and is considered an effective approach to enhance people’s wellbeing. However, large-scale ILR projects often raise a series of social issues in practice, such as injustice and inequality. To address complex urban issues, ILR requires multifaceted, coordinated, and comprehensive strategies involving multitudinous stakeholders. A profound understanding of diverse stakeholders in the decision-making of ILR is a vital step in enhancing the sustainability of ILR. The aim of this paper is to use Shanghai as a case study to understand the diverse stakeholders and their participation during the decision-making of ILR in China. Interviews and questionnaires were used to collect data. Stakeholder analysis (SA) and social network analysis (SNA) were used as complementary research methodologies in this paper. First, stakeholders who participated in the decision-making of ILR were identified. Then, the characteristics of various stakeholders, including power, interests, and knowledge, were analyzed. Following this, the interactive relationships among stakeholders were explored, and their network structure was examined. Finally, policy recommendations were presented regarding stakeholder participation problems in the decision-making of ILR in China.

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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