scholarly journals Construction of Evaluation Index System of University Students’ Innovation Ability Based on Social Network Analysis

2019 ◽  
Author(s):  
Fei Bian
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
University Students ◽  
Index System ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Innovation Ability

scholarly journals A case study of university student networks and the COVID-19 pandemic using a social network analysis approach in halls of residence

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
José Alberto Benítez-Andrades ◽  
Tania Fernández-Villa ◽  
Carmen Benavides ◽  
Andrea Gayubo-Serrenes ◽  
Vicente Martín ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
University Students ◽  
Methodological Approach ◽  
Centrality Measures ◽  
Structural Behaviour ◽  
Cross Sectional ◽  
Depth Analysis ◽  
The University

AbstractThe COVID-19 pandemic has meant that young university students have had to adapt their learning and have a reduced relational context. Adversity contexts build models of human behaviour based on relationships. However, there is a lack of studies that analyse the behaviour of university students based on their social structure in the context of a pandemic. This information could be useful in making decisions on how to plan collective responses to adversities. The Social Network Analysis (SNA) method has been chosen to address this structural perspective. The aim of our research is to describe the structural behaviour of students in university residences during the COVID-19 pandemic with a more in-depth analysis of student leaders. A descriptive cross-sectional study was carried out at one Spanish Public University, León, from 23th October 2020 to 20th November 2020. The participation was of 93 students, from four halls of residence. The data were collected from a database created specifically at the university to "track" contacts in the COVID-19 pandemic, SiVeUle. We applied the SNA for the analysis of the data. The leadership on the university residence was measured using centrality measures. The top leaders were analyzed using the Egonetwork and an assessment of the key players. Students with higher social reputations experience higher levels of pandemic contagion in relation to COVID-19 infection. The results were statistically significant between the centrality in the network and the results of the COVID-19 infection. The most leading students showed a high degree of Betweenness, and three students had the key player structure in the network. Networking behaviour of university students in halls of residence could be related to contagion in the COVID-19 pandemic. This could be described on the basis of aspects of similarities between students, and even leaders connecting the cohabitation sub-networks. In this context, Social Network Analysis could be considered as a methodological approach for future network studies in health emergency contexts.

scholarly journals Identification of cohesive subgroups in a university hall of residence during the COVID-19 pandemic using a social network analysis approach

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Pilar Marqués-Sánchez ◽  
Arrate Pinto-Carral ◽  
Tania Fernández-Villa ◽  
Ana Vázquez-Casares ◽  
Cristina Liébana-Presa ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
University Students ◽  
Global Network ◽  
Case Study Methodology ◽  
And Gender ◽  
The One ◽  
Relationship Structure ◽  
The University

AbstractThe aims: (i) analyze connectivity between subgroups of university students, (ii) assess which bridges of relational contacts are essential for connecting or disconnecting subgroups and (iii) to explore the similarities between the attributes of the subgroup nodes in relation to the pandemic context. During the COVID-19 pandemic, young university students have experienced significant changes in their relationships, especially in the halls of residence. Previous research has shown the importance of relationship structure in contagion processes. However, there is a lack of studies in the university setting, where students live closely together. The case study methodology was applied to carry out a descriptive study. The participation consisted of 43 university students living in the same hall of residence. Social network analysis has been applied for data analysis. Factions and Girvan–Newman algorithms have been applied to detect the existing cohesive subgroups. The UCINET tool was used for the calculation of the SNA measure. A visualization of the global network will be carried out using Gephi software. After applying the Girvan–Newman and Factions, in both cases it was found that the best division into subgroups was the one that divided the network into 4 subgroups. There is high degree of cohesion within the subgroups and a low cohesion between them. The relationship between subgroup membership and gender was significant. The degree of COVID-19 infection is related to the degree of clustering between the students. College students form subgroups in their residence. Social network analysis facilitates an understanding of structural behavior during the pandemic. The study provides evidence on the importance of gender, race and the building where they live in creating network structures that favor, or not, contagion during a pandemic.

scholarly journals Grouping University Students Using Social Network Analysis

2014 ◽  
pp. 54-73
Author(s):  
Alexander Pronin ◽  
◽  
Elena Veretennik ◽  
Alexander Semyonov ◽  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
University Students

scholarly journals A Case Study of Roles in the Social Reading Activities

2021 ◽  
Vol 2 (5) ◽  
Author(s):  
Chen Guo ◽  
Chun Luo
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
University Students ◽  
Knowledge Sharing ◽  
Reading Process ◽  
The Social ◽  
Reading Activities ◽  
Social Reading

Readers who participate in social reading activities can play a variety of roles. These roles can reflect differences in the behaviors among readers and influence the knowledge sharing and information flowing in the social reading process. This study investigates a community of university students’ roles in the WeChat reading activities. Social Network Analysis approach was adopted for analyzing the data in WeChat reading. Results indicate that different roles have different effects on the connection between subgroups and the dissemination of information, which can cause influences on the generation and development of social reading networks as well. This study offers implications for facilitating readers’ interactions and knowledge sharing in the social reading contexts.

scholarly journals Social Network Analysis and Resilience in University Students: An Approach from Cohesiveness

2018 ◽  
Vol 15 (10) ◽  
pp. 2119 ◽  
Author(s):  
Cristina Liébana-Presa ◽  
Elena Andina-Díaz ◽  
María-Mercedes Reguera-García ◽  
Iván Fulgueiras-Carril ◽  
David Bermejo-Martínez ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
University Students ◽  
Support Networks ◽  
Friendship Networks ◽  
Social Phenomena ◽  
The Social ◽  
Minimal Contact ◽  
Transversal Study

The Social Network Analysis offers a view of social phenomena based on interactions. The aim of this study is to compare social reality through the cohesion variable and analyse its relationship with the resilience of university students. This information is useful to work with the students academically and to optimise the properties of the network that have an influence in academic performance. This is a descriptive transversal study with 90 students from the first and third year of the Nursing Degree. Cohesion variables from the support and friendship networks and the level of resilience were gathered. The UCINET programme was used for network analysis and the SPSS programme for statistical analysis. The students’ friendship and support networks show high intra-classroom cohesion although there are no differences between the support networks and friendship or minimal contact networks in both of the courses used for the study. The network cohesion indicators show less cohesion in the third year. No correlations were found between cohesion and resilience. Resilience does not appear to be an attribute related to cohesion or vice versa.

scholarly journals The Evaluation of Synergy between University Entrepreneurship Education Ecosystem and University Students’ Entrepreneurship Performance

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Sheng-Yuan Wang ◽  
Xiao-Lan Wu ◽  
Meng Xu ◽  
Quan-Xin Chen ◽  
Ying-Jing Gu
Keyword(s):  
University Students ◽  
Goal Programming ◽  
Index System ◽  
Entrepreneurship Education ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Volterra Model ◽  
University Entrepreneurship ◽  
College And University ◽  
Performance Evaluation Index

The interactive mechanism between college and university entrepreneurship education ecosystem and their students’ entrepreneurial performance needs to be further discussed, as college and university students are an important force in entrepreneurship. Since there is a lack of symbiotic mechanism analysis and interactive optimization research using ecological methods, this paper constructs the evaluation index system of entrepreneurship education ecosystem and entrepreneurship performance evaluation index system and uses the entropy weight method to determine the weight of various indicators in the index system more objectively. In this paper, Lotka–Volterra model in ecology is used to deeply study the mechanism between college and university entrepreneurship education ecosystem and entrepreneurship performance. Lotka–Volterra multichoice goal programming (MCGP) model is used to optimize the collaborative relationship between college and university entrepreneurship education ecosystem and entrepreneurship performance. Finally, a numerical example is given to illustrate the feasibility and effectiveness of the research method. The results show that Lotka–Volterra multichoice goal programming (MCGP) method is effective in evaluating the synergy between college and university entrepreneurship education ecosystem and the students’ entrepreneurship performance.

scholarly journals Evaluation of Innovation Ability of Industrial Clusters Based on BP Neural Network

2021 ◽  
Vol 2074 (1) ◽  
pp. 012091
Author(s):  
Chunjie Fang
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Index System ◽  
International Competitiveness ◽  
Industrial Clusters ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Innovation Ability

Abstract In order to improve the innovation ability of enterprises and enhance international competitiveness, it is necessary to correctly analyze and evaluate the innovation ability of industrial clusters. Therefore, BP neural network is used to explain the innovation ability of industrial clusters, and the evaluation index system is established. By investigating industrial clusters and using it to provide references for the evaluation of industrial clusters’ innovation capabilities.

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