Efficient Approximation Algorithms for Minimum Dominating Sets in Social Networks

Author(s):  
Traian Marius Truta ◽  
Alina Campan ◽  
Matthew Beckerich

Social networks are increasingly becoming an outlet that is more and more powerful in spreading news and influence individuals. Compared with other traditional media outlets such as newspaper, radio, and television, social networks empower users to spread their ideological message and/or to deliver target advertising very efficiently in terms of both cost and time. In this article, the authors focus on efficiently finding dominating sets in social networks for the classical dominating set problem as well as for two related problems: partial dominating sets and d-hop dominating sets. They will present algorithms for determining efficiently a good approximation for the social network minimum dominating sets for each of the three variants. The authors ran an extensive suite of experiments to test the presented algorithms on several datasets that include real networks made available by the Stanford Network Analysis Project and synthetic networks that follow the power-law and random models that they generated for this work. The performed experiments show that the selection of the algorithm that performs best to determine efficiently the dominating set is dependent of network characteristics and the order of importance between the size of the dominating set and the time required to determine such a set.

Author(s):  
Traian Marius Truta ◽  
Alina Campan ◽  
Matthew Beckerich

Social networks are increasingly becoming an outlet that is more and more powerful in spreading news and influence individuals. Compared with other traditional media outlets such as newspaper, radio, and television, social networks empower users to spread their ideological message and/or to deliver target advertising very efficiently in terms of both cost and time. In this article, the authors focus on efficiently finding dominating sets in social networks for the classical dominating set problem as well as for two related problems: partial dominating sets and d-hop dominating sets. They will present algorithms for determining efficiently a good approximation for the social network minimum dominating sets for each of the three variants. The authors ran an extensive suite of experiments to test the presented algorithms on several datasets that include real networks made available by the Stanford Network Analysis Project and synthetic networks that follow the power-law and random models that they generated for this work. The performed experiments show that the selection of the algorithm that performs best to determine efficiently the dominating set is dependent of network characteristics and the order of importance between the size of the dominating set and the time required to determine such a set.


Author(s):  
Khalid Abdulkareem Al-Enezi ◽  
Imad Fakhri Taha Al Shaikhli ◽  
Sufyan Salim Mahmood AlDabbagh

<span>This research aims to measure the role of social networks in influencing purchasing decisions among consumers in Kuwait; the research used the quantitative methods, and analytical the technique to get the results, and the research developed a measure to study the relationship between the variables to the study and selection of a sample of consumers of (100). The results indicated that the social networking variables (exchange of information, evaluation of product) possess influence on purchasing decisions. Furthermore, the results indicate that majority of respondents do their digital scanning more often before intend to go to the store. The unexpected results came from the question “traditional advertising (TV, Newspaper, Magazine, Billboards) are more effective than the social networking; 23% agreed, 36% said no, and 41% said sometimes. In light of these findings, the study made a series of recommendations; the most important are; The executives and sales representatives need to understand the benefits offered by social networks, and understand the advantages and functions and tools of social communication, and knowing how to apply them effectively and efficiently, and then use the appropriate social networking tool.</span>


Children ◽  
2022 ◽  
Vol 9 (1) ◽  
pp. 113
Author(s):  
Sarah E. Wawrzynski ◽  
Melissa A. Alderfer ◽  
Whitney Kvistad ◽  
Lauri Linder ◽  
Maija Reblin ◽  
...  

Siblings of children with cancer need support to ameliorate the challenges they encounter; however, little is known about what types and sources of support exist for siblings. This study addresses this gap in our understanding of the social networks and sources of support for adolescents with a brother or sister who has cancer. Additionally, we describe how the support siblings receive addresses what they feel are the hardest aspects of being a sibling of a child with cancer. During semi-structured interviews, siblings (ages 12–17) constructed ecomaps describing their support networks. Data were coded for support type (emotional, instrumental, informational, validation, companionship) and support provider (e.g., mother, teacher, friend). Network characteristics and patterns of support were explored. Support network size ranged from 3 to 10 individuals (M = 6 ± 1.9); siblings most frequently reported mothers as sources of support (n = 22, 91.7%), followed by fathers (n = 19, 79.2%), close friends (n = 19, 79.2%) and siblings (with or without cancer) (n = 17, 70.8%). Friends and brothers or sisters most often provided validation and companionship while instrumental and informational supports came from parents. This study provides foundational knowledge about siblings’ support networks, which can be utilized to design interventions that improve support for siblings of children with cancer.


2021 ◽  
pp. 163-173
Author(s):  
S. G. Ushkin ◽  
V. G. Ushkina

The article substantiates the idea of transformation of public policy in modern Russia, which is associated with the processes of digitalization of both power structures and the population as a whole. Practices of self-representation of governors in the virtual network space are considered. Based on an original approach based on the methodological principles of P. Lazarsfeld, J. Habermas, P. Bourdieu, and E. Goffman examines the popularity of the accounts, the frequency of their updates, the level of social approval records, feedback, etc., and also visual settings — formal or informal nature of the shooting the main photo in the profile, the social distance on it, head position and gaze, emotional background. We use our own data collected in December 2019. Based on the information received, it is concluded that representatives of the Governor’s corps and users of virtual social networks understand the importance of digital transformations of public policy, although this is not directly expressed in expert assessments of their activities. In some cases, governors are effective leaders of public opinion, whose number of subscribers exceeds the audience of many regional traditional media. Also, many of them create conditions for an equal dialogue with the population, independently or with the help of assistants responding to incoming requests.


2021 ◽  
Vol 32 (1) ◽  
pp. 193-196
Author(s):  
Ilire Zajmi

Social media are changing the nature of mass communication, demediating traditional media. They are being used as powerful platforms for the distribution and dissemination of information, activities, promotion of institutions, certain groups of interest of individuals, but also political actors for different purposes.Placing and disseminating information through the opportunities offered by social media enables the mobilization of a wider audience in new ways and ways. Politicians are exploiting these opportunities provided by social networks, without having to put information through journalists or traditional media. There are two theories in the literature regarding the use of social networks, optimistic and pessimistic theory. According to optimistic theory, social networks provide opportunities to compete for power. Theorists of this theory of using social media think that in the digital age, we are witnessing the transformation of information and the audience that uses them. According to them, the global success of social media has made it possible for everyone to connect directly to his audience through the platforms offered. With the use of these platforms, politicians gain attention and at the same time build a symmetrical or asymmetric relationship with their followers.Pessimistic theory, however, blames the social media for the use of false promise, and a pseudo-modernization of modern society. Studies believe that involvement in social networks and political actors at the same time implies a greater engagement of the audience that absorbs the information disclosed and affects the democratization of political competition. This paper aims to analyze the use of social networks as a means of information dissemination by Kosovar political actors and the content of the information being disclosed.The paper analyzes the posts of three key Kosovar politicians, Prime Minister Ramush Haradinaj, President Hashim Thaçi and Kosovo Assembly Speaker Kadri Veseli in their profiles on Facebook and Twitter social networks during a one-month monitoring period during May 2019


Algorithms ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 79
Author(s):  
Salim Bouamama ◽  
Christian Blum

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.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Irfan Nazeer ◽  
Tabasam Rashid ◽  
Juan Luis Garcia Guirao

Fuzzy graphs (FGs), broadly known as fuzzy incidence graphs (FIGs), have been recognized as being an effective tool to tackle real-world problems in which vague data and information are essential. Dominating sets (DSs) have multiple applications in diverse areas of life. In wireless networking, DSs are being used to find efficient routes with ad hoc mobile networks. In this paper, we extend the concept of domination of FGs to the FIGs and show some of their important properties. We propose the idea of order, size, and domination in FIGs. Two types of domination, namely, strong fuzzy incidence domination and weak fuzzy incidence domination, for FIGs are discussed. A relationship between strong fuzzy incidence domination and weak fuzzy incidence domination for complete fuzzy incidence graphs (CFIGs) is also introduced. An algorithm to find a fuzzy incidence dominating set (FIDS) and a fuzzy incidence domination number (FIDN) is discussed. Finally, an application of fuzzy incidence domination (FID) is provided to choose the best medical lab among different labs for the conduction of tests for the coronavirus.


2018 ◽  
Author(s):  
Thabo J van Woudenberg ◽  
Bojan Simoski ◽  
Eric Fernandes de Mello Araújo ◽  
Kirsten E Bevelander ◽  
William J Burk ◽  
...  

BACKGROUND Social network interventions targeted at children and adolescents can have a substantial effect on their health behaviors, including physical activity. However, designing successful social network interventions is a considerable research challenge. In this study, we rely on social network analysis and agent-based simulations to better understand and capitalize on the complex interplay of social networks and health behaviors. More specifically, we investigate criteria for selecting influence agents that can be expected to produce the most successful social network health interventions. OBJECTIVE The aim of this study was to test which selection criterion to determine influence agents in a social network intervention resulted in the biggest increase in physical activity in the social network. To test the differences among the selection criteria, a computational model was used to simulate different social network interventions and observe the intervention’s effect on the physical activity of primary and secondary school children within their school classes. As a next step, this study relied on the outcomes of the simulated interventions to investigate whether social network interventions are more effective in some classes than others based on network characteristics. METHODS We used a previously validated agent-based model to understand how physical activity spreads in social networks and who was influencing the spread of behavior. From the observed data of 460 participants collected in 26 school classes, we simulated multiple social network interventions with different selection criteria for the influence agents (ie, in-degree centrality, betweenness centrality, closeness centrality, and random influence agents) and a control condition (ie, no intervention). Subsequently, we investigated whether the detected variation of an intervention’s success within school classes could be explained by structural characteristics of the social networks (ie, network density and network centralization). RESULTS The 1-year simulations showed that social network interventions were more effective compared with the control condition (beta=.30; t100=3.23; P=.001). In addition, the social network interventions that used a measure of centrality to select influence agents outperformed the random influence agent intervention (beta=.46; t100=3.86; P<.001). Also, the closeness centrality condition outperformed the betweenness centrality condition (beta=.59; t100=2.02; P=.046). The anticipated interaction effects of the network characteristics were not observed. CONCLUSIONS Social network intervention can be considered as a viable and promising intervention method to promote physical activity. We demonstrated the usefulness of applying social network analysis and agent-based modeling as part of the social network interventions’ design process. We emphasize the importance of selecting the most successful influence agents and provide a better understanding of the role of network characteristics on the effectiveness of social network interventions.


Author(s):  
Ramiro Rodrigues Sumar

Objective: To describe the impact that social networks can have on the recruitment and selection of their employees. Question Problem: How can the social network favor the recruitment and selection of employees of a company? Methodology: Literature review. Results: The evidence of the results showed that technologies through social networks can be relevant for the recruitment and selection of people for the organization. But this recruitment should be done with a differentiated look at each type of social network by the recruiter. Final Considerations: Recruitment and selection have been changing as a traditional (face-to-face) way for the technological (virtual) mode. The study mentioned that social networks are tools capable of bringing to the recruiter candidates able to take the organization responsibly and that there are no barriers in the virtual world to find the ideal candidate. It is emphasized the importance of extending this study based on scientific evidence, in which research can be carried out in companies for the use of social networks in the monitoring of their employees.


Sign in / Sign up

Export Citation Format

Share Document