Finding Weighted Positive Influence Dominating Set to Make Impact to Negatives: A Study on Online Social Networks in the New Millennium

2014 ◽  
pp. 67-80 ◽  
Author(s):  
Guangyuan Wang ◽  
Hua Wang ◽  
Xiaohui Tao ◽  
Ji Zhang
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Dominating Set ◽  
Positive Influence ◽  
New Millennium

scholarly journals On the approximability of positive influence dominating set in social networks

2012 ◽  
Vol 27 (3) ◽  
pp. 487-503 ◽  
Author(s):  
Thang N. Dinh ◽  
Yilin Shen ◽  
Dung T. Nguyen ◽  
My T. Thai
Keyword(s):  
Social Networks ◽  
Dominating Set ◽  
Positive Influence

The Influence of (Online) Social Networks on Workers' Attitudes and Behaviours in Higher Education Institutions

2017 ◽  
pp. 644-666
Author(s):  
Vera Silva Carlos ◽  
Ricardo Gouveia Rodrigues
Keyword(s):  
Higher Education ◽  
Social Networks ◽  
Web 2.0 ◽  
Online Social Networks ◽  
Higher Education Institutions ◽  
Positive Influence ◽  
Faculty Members ◽  
Future Research ◽  
Work Related ◽  
Considerable Impact

According to the literature, social relationships have a positive influence on work-related attitudes and behaviours. Taking into account that Online Social Networks (OSNs), brought about by Web 2.0, have become an international phenomena and have a considerable impact on the way people communicate and interact with each other, the chapter's purpose is to evaluate the effect that the use of OSNs has on the worker's attitudes and behaviours. In this way, the authors use a questionnaire to evaluate the attitudes of 157 faculty members in Higher Education Institutions (HEI). To assess the use of OSNs by faculty members, they use a binary variable. After analysing and discussing the results, the authors conclude that the use of OSNs influences the workers' performance traits. The relations they propose in what concerns the workers' attitudes are all empirically proven. At last, the authors describe the study limitations and suggest some perspectives for future research.

scholarly journals An Improved Greedy Heuristic for the Minimum Positive Influence Dominating Set Problem in Social Networks

Algorithms ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 79
Author(s):  
Salim Bouamama ◽  
Christian Blum
Keyword(s):  
Social Networks ◽  
Greedy Algorithm ◽  
Dominating Set ◽  
Positive Influence ◽  
Greedy Heuristic ◽  
Greedy Heuristics ◽  
Small Subset ◽  
Problem Size ◽  
Wide Range ◽  
Dominating Set Problem

This paper presents a performance comparison of greedy heuristics for a recent variant of the dominating set problem known as the minimum positive influence dominating set (MPIDS) problem. This APX-hard combinatorial optimization problem has applications in social networks. Its aim is to identify a small subset of key influential individuals in order to facilitate the spread of positive influence in the whole network. In this paper, we focus on the development of a fast and effective greedy heuristic for the MPIDS problem, because greedy heuristics are an essential component of more sophisticated metaheuristics. Thus, the development of well-working greedy heuristics supports the development of efficient metaheuristics. Extensive experiments conducted on a wide range of social networks and complex networks confirm the overall superiority of our greedy algorithm over its competitors, especially when the problem size becomes large. Moreover, we compare our algorithm with the integer linear programming solver CPLEX. While the performance of CPLEX is very strong for small and medium-sized networks, it reaches its limits when being applied to the largest networks. However, even in the context of small and medium-sized networks, our greedy algorithm is only 2.53% worse than CPLEX.

scholarly journals Finding a Weighted Positive In uence Dominating Set in E-learning Social Networks

2013 ◽  
Vol 10 (10) ◽  
pp. 2136-2145 ◽  
Author(s):  
Guangyuan Wang ◽  
Hua Wang ◽  
Xiaohui Tao ◽  
Ji Zhang ◽  
Guohun Zhu
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Learning Community ◽  
Dominating Set ◽  
Online Social Network ◽  
Real Life ◽  
Synthetic Data ◽  
Positive Influence ◽  
Data Sets ◽  
E Learning

Online social network has developed significantly in recent years. Most of current research has utilized the property of online social network to spread information and ideas. Motivated by the applications of dominating set in social networks (such as e-learning), a variation of the dominating set called positive influence dominating set (PIDS) has been studied in the literature. The existing research for PIDS problem do not take into consideration the attributes, directions and degrees of personal influence. However, these factors are very important for selecting a better PIDS. For example, in a real-life e-learning community, the attributes and the degrees of their influence between a tutor and a student are different; the relationship between two e-learning users is asymmetrical. Hence, comprehensive, deep investigation of user’s properties become an emerging and urgent issue. The focus of this study is on the degree and direction between e-learners’ influence. A novel dominating set model called weighted positive influence dominating set (WPIDS), and two selection algorithms for the WPIDS problem have been proposed. Experiments using synthetic data sets demonstrate that the proposed model and algorithms are more reasonable and effective than those of the positive influence dominating set (PIDS) without considering the key factors of weight, direction and so on.

The Use of Online Social Networks and Its Influence on Job-Related Behavior

2019 ◽  
pp. 106-129
Author(s):  
Vera Silva Carlos ◽  
Ricardo Gouveia Rodrigues
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Online Survey ◽  
Positive Influence ◽  
Future Research ◽  
Work Related ◽  
Attitudes And Behaviors ◽  
Empirically Supported ◽  
And Behaviors ◽  
And Behavior

Web 2.0 technologies have progressively transformed social interactions among people. In addition, there is plenty of evidence of a positive influence of social relationships on work-related attitudes and behaviors. Within these frameworks, the purpose is to evaluate the effect of using online social networks on the workers' attitudes and behaviors, particularly in the context of higher education. The authors used an online survey to evaluate the attitudes and behavior of 157 faculty members. To assess the use of OSNs, they used a dichotomous variable. The t-student test and the PLS method were used to analyze the data. They conclude that the use of OSNs influences the workers' performance, but not job satisfaction, organizational commitment, or organizational citizenship behaviors (extra-role performance). The relationships they propose in what concerns the workers' attitudes are all empirically supported. Lastly, they describe the study limitations and we suggest some perspectives for future research.

The Use of Online Social Networks in Higher Education and Its Influence on Job Performance

2016 ◽  
pp. 330-353
Author(s):  
Vera Silva Carlos ◽  
Ricardo Gouveia Rodrigues
Keyword(s):  
Higher Education ◽  
Social Networks ◽  
Online Social Networks ◽  
Positive Influence ◽  
Future Research ◽  
Work Related ◽  
Attitudes And Behaviors ◽  
Dichotomous Variable ◽  
Considerable Impact ◽  
And Behaviors

There is plenty of evidence on a positive influence of social relationships on work-related attitudes and behaviors. Besides, online social networks (OSNs), made possible by Web 2.0, have become a global phenomenon and have a considerable impact on the way people communicate and interact with each other. Our purpose is to evaluate the effect of using OSNs on the worker's attitudes and behaviors, particularly in the context of Higher Education. In this sense, we used a questionnaire, to evaluate the attitudes of 157 faculty members. To assess the use of OSNs, we resorted to a dichotomous variable. After analyzing and discussing the results we conclude that the use of OSNs influences the worker's performance, but not Job satisfaction, Organizational commitment or extra-role performance. The relationships we propose in what concerns the worker's attitudes are all empirically proved. Lastly, we describe the study limitations and we suggest some perspectives for future research.

Sign in / Sign up

Export Citation Format

Share Document