scholarly journals A scoping review using social network analysis techniques to summarise the prevalance of methods used to acquire data for athlete survelliance in sport

2021 ◽  
Vol 20 (2) ◽  
pp. 175-197
Author(s):  
P. J. Watson ◽  
J. E. Fieldsend ◽  
V.H. Stiles
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Scoping Review ◽  
Data Driven ◽  
Surveillance Systems ◽  
Analysis Techniques ◽  
Access Information ◽  
Visual Resource ◽  
Selection Of

Abstract To aid the implementation of athlete surveillance systems relative to logistical circumstances, easy-to-access information that summarises the extent to which methods of acquiring data are used in practice to monitor athletes is required. In this scoping review, Social Network Analysis and Mining (SNAM) techniques were used to summarise and identify the most prevalent combinations of methods used to monitor athletes in research studying team, individual, field- and court-based sports (357 articles; SPORTDiscus, MEDLINE, CINHAL, and WebOfScience; 2014-2018 inc.) . The most prevalent combination in team and field-based sports were HR and/or sRPE (internal) and GPS, whereas in individual and court-based sports, internal methods (e.g., HR and sRPE) were most prevalent. In court-based sports, where external methods were occasionally collected in combination with internal methods of acquiring data, the use of accelerometers or inertial measuring units (ACC/IMU) were most prevalent. Whilst individual and court-based sports are less researched, this SNAM-based summary reveals that court-based sports may lead the way in using ACC/IMU to monitor athletes. Questionnaires and self-reported methods of acquiring data are common in all categories of sport. This scoping review provides coaches, sport-scientists and researchers with a data-driven visual resource to aid the selection of methods of acquiring data from athletes in all categories of sport relative to logistical circumstances. A guide on how to practically implement a surveillance system based on the visual summaries provided herein, is also presented.

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 Social Network Analysis in Healthcare Settings: A Systematic Scoping Review

PLoS ONE ◽  
2012 ◽  
Vol 7 (8) ◽  
pp. e41911 ◽  
Author(s):  
Duncan Chambers ◽  
Paul Wilson ◽  
Carl Thompson ◽  
Melissa Harden
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Scoping Review ◽  
Healthcare Settings

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 Basic Criteria, Models, and Indicators of Intersectoral Collaboration in Health Promotion: A Scoping Review

2021 ◽  
Author(s):  
Mohammad Reza Amir Esmaili ◽  
Behzad Damari ◽  
Ahmad Hajebi ◽  
Noora Rafiee ◽  
Reza Goudarzi ◽  
...  
Keyword(s):  
Health Promotion ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Scoping Review ◽  
Web Of Science ◽  
Decision Makers ◽  
Macro Level ◽  
Intersectoral Collaboration ◽  
Micro Level

Background: In this study, the basic criteria, models, and indicators of intersectoral collaboration in health promotion were investigated to facilitate the implementation of collaboration. Methods: This scoping review was conducted using datasets of Embase, Web of Science, Scopus, and PubMed, and search engines of Google, Google Scholar, and ProQuest. Results: 52 studies were included, and 32 codes in Micro, Meso, and Macro level, were obtained. Micro-level criteria had the highest frequency. Among the models used in the reviewed studies, social network analysis, Diagnosis of Sustainable Collaboration, Bergen, and logic models had the highest frequency. Among the indicators studied, the number of participants and the level of collaboration as well as its sustainability were the most frequent indicators. Conclusion: The findings identified the most important and widely used criteria, models, and indicators of intersectoral collaboration in health promotion which can be useful for decision-makers and planners in the domain of health promotion, in designing, implementing, and evaluating collaborative programs.

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.

scholarly journals A scoping review on the current and potential use of social network analysis for evaluation purposes

Evaluation ◽  
2018 ◽  
Vol 24 (3) ◽  
pp. 325-352 ◽  
Author(s):  
Lisa Popelier
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Scoping Review ◽  
Social Science Research ◽  
Science Research ◽  
Network Structures ◽  
Alternative Sources ◽  
Informal Relations ◽  
Potential Use

The pervasiveness and importance of relationships and networks has fueled the development of the social network analysis approach, which considers structural relationships to be primary causes of societal outcomes. While the potential of social network analysis has been demonstrated and discussed extensively in social science research, relatively little is known about the current and potential use of social network analysis for evaluation purposes. This scoping review of journal articles reveals that evaluators use social network analysis because of its ability to identify key stakeholders, assess network structures and relationships quantitatively, reveal informal relations and visualize even complex networks. However, challenges arise when interpreting findings, determining causation between network structures and outcomes and disseminating evaluation results in an ethically responsible manner. The review concludes that the evaluation field―especially in the development sector―would benefit greatly from increased use of social network analysis, but that this would first require improved use of alternative sources of network data, qualitative methods and inferential statistics that will enable evaluators to move beyond descriptive network analysis.

Pair Selection of Appropriate Taxi Drivers Using Social Network Analysis Models

2018 ◽  
Author(s):  
Chawit Rujichansiri ◽  
Kwanchai Kungcharoen ◽  
Prajin Palangsantikul ◽  
Parham Porouhan ◽  
Wichian Premchaiswadi
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Taxi Drivers ◽  
Analysis Models ◽  
Selection Of
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