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Showing papers on "Social network published in 2022"


Journal ArticleDOI
TL;DR: In this paper, the authors propose the "Supply and demand" framework for analyzing YouTube users' behavior and find that YouTube is more popular among right-leaning users than other major social networks.
Abstract: YouTube is the most used social network in the United States and the only major platform that is more popular among right-leaning users. We propose the “Supply and Demand” framework for analyzing p...

63 citations


Journal ArticleDOI
TL;DR: In this paper, a dynamic generalized genetic algorithm (GDGA) was used to obtain a dynamic seed set in social networks under independent cascade models to identify influential nodes in these snapshot graphs.
Abstract: Over the recent decade, much research has been conducted in the field of social networks. The structure of these networks has been irregular, complex, and dynamic, and certain challenges such as network topology, scalability, and high computational complexities are typically evident. Because of the changes in the structure of social networks over time and the widespread diffusion of ideas, seed sets also need to change over time. Since there have been limited studies on highly dynamical changes in real networks, this research intended to address the network dynamicity in the classical influence maximization problem, which discovers a small subset of nodes in a social network and maximizes the influence spread. To this end, we used soft computing methods (i.e., a dynamic generalized genetic algorithm) in social networks under independent cascade models to obtain a dynamic seed set. We modeled several graphs in a specified timestamp through which the edges and the nodes changed within different time intervals. Attempts were made to find influential individuals in each of these graphs and maximize individuals’ influences in social networks, which could thereby lead to changes in the members of the seed set. The proposed method was evaluated using standard datasets. The results showed that due to the reduction of the search areas and competition, the proposed method has higher scalability and accuracy to identify influential nodes in these snapshot graphs as compared with other comparable algorithms.

30 citations


Journal ArticleDOI
TL;DR: This paper introduces the concept of local world opinion derived from individuals’ common friends, and then proposes an individual and local world Opinion-based OD model, which is jointly determined by the distance between individual opinions and network structure similarity.

24 citations


Journal ArticleDOI
TL;DR: Four major elements of the data collection process are identified and discussed, all linked with and dependent on the specific research question and objective: negotiating access to the organization; identifying the network’s boundary, the relevant formal organizational structures that affect social networks, and the sampling approach.

16 citations


Journal ArticleDOI
TL;DR: In this paper, the authors examined four social interactional mechanisms underlying a user's adoption of political swearing: generalized reciprocity, direct reciprocity and leader mimicry, and peer-mimicry.

13 citations


Book ChapterDOI
TL;DR: This chapter summarizes some of the centrality measures that are extensively applied for mining social network data and discusses various directions of research related to these measures.
Abstract: Experts from several disciplines have been widely using centrality measures for analyzing large as well as complex networks. These measures rank nodes/edges in networks by quantifying a notion of the importance of nodes/edges. Ranking aids in identifying important and crucial actors in networks. In this chapter, we summarize some of the centrality measures that are extensively applied for mining social network data. We also discuss various directions of research related to these measures.

11 citations


Journal ArticleDOI
TL;DR: In this paper, the authors investigate the impact of problematic social network use on course performance and find that too much of a good thing can negatively impact course performance. But, they do not investigate the relationship between problematic social networks and course performance as measured by final letter grade.
Abstract: The impact of information technologies has radically transformed the classroom in less than a generation. One potentially not so welcome technology into the classroom has been social networking sites. While social networking sites can help foster relationships among students, too much of a good thing can negatively impact course performance. This study surveys 219 college aged students and investigates the impact of problematic social network use on final course performance. Drawing from Social Cognitive Theory this paper develops a set of testable hypotheses and the data demonstrates that a negative relationship exists between problematic social network use and course performance (as measured by final letter grade). Classroom strategies that professors implement, and other remedies universities can employ to address this finding are discussed.

9 citations


Journal ArticleDOI
TL;DR: Zhang et al. as discussed by the authors provided new evidence on the dynamics of social capital across the life course and over different periods in urban China using three cross-sectional datasets from the Job Search and Social Network survey (1999, 2009, and 2014).

7 citations


Journal ArticleDOI
TL;DR: Wang et al. as discussed by the authors proposed a multi-objective optimization method to detect community structures in dynamic networks, and the probability fusion method is added to the initial step of the algorithm to generate suitable network partitions and ensure fast convergence and high accuracy.

7 citations


Proceedings ArticleDOI
31 Jan 2022
TL;DR: In this article, social media platforms play a significant role in networking and influencing the perception of the general population in today's era of digitization, and social network sites have recently been used t...
Abstract: In today’s era of digitization, social media platforms play a significant role in networking and influencing the perception of the general population. Social network sites have recently been used t...

7 citations


Journal ArticleDOI
TL;DR: In this article, the authors examined how the distance to social alters may lead to different perceptions of neighborhood and city attachment among urban versus rural residents, and considered which types of relations play influential roles in shaping attachment.

Journal ArticleDOI
TL;DR: Wang et al. as mentioned in this paper proposed a hybrid information fusion approach for friend prediction based on the characteristics of social media, which extracts the content topics of microblog for each participant along with the appraisal of domain-dependent user impact, builds a small-size heterogeneous network for each target user by fusing the interest similarity and social interaction between individuals, discovers all of the implicit clusters of target user via a community detection algorithm, and establishes the recommendation set consisting of a fixed number of potential friends.

Journal ArticleDOI
TL;DR: In this paper, the authors proposed an SIR knowledge dissemination model with enterprise social media and offline transmission routes in the multiplex network, and the results demonstrate that if the review rate of the knowledge is smaller, the speed of dissemination of knowledge is slower and the scope of dissemination is smaller.
Abstract: The enterprise social media and the offline social network are the two main routes to disseminate the knowledge among employees in the enterprise. In this study, we propose an SIR knowledge dissemination model with enterprise social media and offline transmission routes in the multiplex network. Through the analysis and calculation, we obtain the threshold to distinguish whether a certain knowledge is disseminated or not in the multiplex network. Simulation experiments are carried out. The results demonstrate that if the review rate of the knowledge is smaller, the speed of dissemination of the knowledge is slower and the scope of dissemination of the knowledge is smaller. If employees appropriately use two routes to disseminate the knowledge comparing with only use one of the two routes, the speed of dissemination is faster and the scope of dissemination is wider. In addition, enterprise social media cannot replace offline transmission route completely in the dissemination of the knowledge. The face to face communication among employees by using offline transmission route still plays an important role. We also find that the efficiency of dissemination in the multiplex network with enterprise social media (scale-free sub-network) and offline transmission route (homogeneous sub-network) is higher than the efficiency of dissemination in the multiplex network with enterprise social media (homogeneous sub-network) and offline transmission route (homogeneous sub-network).

Journal ArticleDOI
TL;DR: In this article, two studies were conducted in conflict-affected eastern Democratic Republic of the Congo (DRC) and broadly aimed to refine understandings of public authority and governance, focusing on access to essential social services across different governance arrangements.

Journal ArticleDOI
TL;DR: The effect of celebrity is introduced, under which a player behaves more generous or stingier when faces different opponents, and shows that if ordinary people tend to be more generous to celebrities and celebrities are stingier to the ordinary, fairness will be enhanced first and gradually evolves to an over-fair level.
Abstract: The evolutionary ultimatum game is a powerful paradigm to study the evolution of fairness. Most studies to date assume that a player adopts the same strategy against all his/her opponents. Apart from these works, there are also works exploring the evolution of fairness when various psychological and social factors influence strategies, but celebrity has never been considered. In this paper, we introduce the effect of celebrity, under which a player behaves more generous or stingier when faces different opponents. The celebrity of individuals in a social network is defined as their degree, and ordinary people have small degrees while celebrities have large degrees. The result shows that if ordinary people tend to be more generous to celebrities and celebrities are stingier to the ordinary, fairness will be enhanced first and gradually evolves to an over-fair level.

Journal ArticleDOI
TL;DR: Wang et al. as discussed by the authors proposed a novel Framework of Integrating both Latent and Explicit features (FILE), to better deal with the no-relation status and hence improve the overall trust/distrust prediction performance.

Journal ArticleDOI
TL;DR: In this article, the authors explored how persons living with brain tumors and informal caregivers perceive the potential usefulness of a social network-mapping tool in their self-care and to describe the qualities in the interpersonal relations that they map.

Journal ArticleDOI
TL;DR: In this article, a model of influence spreading for analysing human behaviour and interaction with others in a social network was developed and applied to real data of mobile phone call detail records.
Abstract: In an earlier study one of us had developed a model of influence spreading for analysing human behaviour and interaction with others in a social network. Here we apply this model and corresponding influence centrality measures to real data of mobile phone call detail records. From this we get structures of human ego-centric networks and use a simple model, based on the number of phone calls, to describe the strengths of social relationships. To analyse 48,000 egos in their ego-centric networks we define normalised out-centrality and in-centrality influence measures, by dividing with out-degree and in-degree, respectively. With these and the betweenness centrality measures, we analyse the influence spreading in the ego-centric networks under different scenarios of link strengths between individuals reflecting the network structure being either interaction or connectivity oriented. The model reveals characteristics of social behaviour that are not obvious from the data analysis of raw empirical data or from the results of standard centrality measures. A transition is discovered in behaviour from young to older age groups for both genders and in both normalised out-centrality and in-centrality as well as betweenness centrality results.


Journal ArticleDOI
TL;DR: This article examined the role of social context (social network structure and composition) in people's intentions to prepare for a hurricane and found that people with more dense social networks and more emotionally close network compositions were more likely to evacuate regardless of its severity.

Journal ArticleDOI
TL;DR: In this paper, the authors explored how the interdependency of the interorganizational level can influence the dynamic of endogenous structuration of interpersonal relations in a collaboration network among companies and an advice network among directors from a Brazilian knowledge intensive technological cluster.

Book ChapterDOI
01 Jan 2022
TL;DR: In this article, a social network mining model is proposed to evaluate and forecast user's trust in order to prevent malicious users from developing fake accounts, and the proposed work mines text data and metadata on Twitter accounts to achieve the spammicity classification of the user.
Abstract: The distribution of information in social media is very ad hoc in nature because of the increasing social media and the sophistication of social networks. Identifying fraudulent accounts is one of the key security issues. The task of identifying the reputation of social media users is difficult. In order to prevent malicious users from developing fake accounts, a social network mining model is suggested to evaluate and forecast user's trust. The proposed work mines text data and metadata on Twitter accounts to achieve the spammicity classification of the user. To evaluate the optimal characteristics that lead to optimizing the classification accuracy, the recursive Feature Elimination technique is used. The proposed work is evaluated on a real-time Twitter dataset and the empirical findings indicate that the proposed method performs better.

Journal ArticleDOI
TL;DR: In this article, user recommendation aims at recommending users with potential interests in the social network by recommending users that have potential interest in a social network and recommending the users with the most relevant interests.
Abstract: User recommendation aims at recommending users with potential interests in the social network. Previous works have mainly focused on the undirected social networks with symmetric relationship such ...

Book ChapterDOI
01 Jan 2022
TL;DR: The chapter considers social networking beyond networking sites and applications, and hence a discussion on privacy threats for sensitive data which spread across fields such as health data, forensic, smart toys, image and video surveillance is also analyzed.
Abstract: Social networking creates relationships through the internet and it gains indivisible relation with human life nowadays. Social networking sites and applications handle a large volume of data. As more personal information flows in and out of social networks, data privacy and security in the social network become a topic of discussion and arguments. This chapter emphasizes data privacy and also differentiates privacy from security. Initial sections of the chapter explain privacy in its elementary form as a need and right of a human being under the perspective of anthropology and behavioral science. Personal data privacy, its current scenario, threats and its protection by law and policymaking by various governments around the world are discussed further. The chapter considers social networking beyond networking sites and applications, and hence a discussion on privacy threats for sensitive data which spread across fields such as health data, forensic, smart toys, image and video surveillance is also analyzed. Positives and negatives of social network’s underlying technologies, like machine learning, artificial intelligence, data sciences, the internet of things and blockchain are discussed in terms of data privacy. The personal data privacy measures imposed by law that need to be incorporated as the part of privacy policies of organizations or that need to be implemented with the support of data security mechanisms are discussed in the last part of the chapter.

Journal ArticleDOI
TL;DR: This paper proposes a larger set of criteria than existing related works, and the use of subjective logic to represent and combine subjective and objective scores, aiming at improving accuracy and precision in trust estimation.

Book ChapterDOI
01 Jan 2022
TL;DR: In this paper, a framework to classify a Facebook profile as genuine or fake using machine learning techniques is proposed and the same framework will be used for the prediction of stalking, which can harm the reputation and invade privacy in online social platform.
Abstract: The increasing popularity and demand of social media has resulted in connecting people across the globe in a better way. The use of social media platforms to express their views and showcase their day-to-day life is increasing gradually. The activities related to social, business, entertainment and information are being exchanged regularly in social networking. In case of Facebook, there are approximately 1.5 billion users and this count is increasing daily. More than 10 million likes and shares are performed daily on Facebook. Many other networks, like LinkedIn, Instagram, Twitter, Snapchat, etc., are also growing exponentially. But, with all the advancements and growth, several problems are also introduced. Facebook has its own benefits to people but at the same time Facebook is being targeted for many malicious activities such as creating fake profiles to stalk people, online impersonation, etc., which can harm the reputation and invade privacy in online social platform. One of the challenging problems in social network security is to recognize the fake profiles. This has resulted in need of cybersecurity measures and applications to prevent people from cyberbullying such as stalking from fake profiles. In this paper, a framework to classify a Facebook profile as genuine or fake using machine learning techniques is proposed and the same framework will be used for the prediction of stalking.


Journal ArticleDOI
TL;DR: In this paper, the authors focus on one critical characteristic of SNS platform, SNS transparency, and investigate its impact (direct and indirect via Information Control) on individuals' self-disclosure intention and the moderating role of privacy disposition.

Journal ArticleDOI
TL;DR: In this article, the effect of cohabiting life partners' attitudes, resources, and social network compositions on their spouse's interethnicity was studied considering both non-migrant and migrant couples.
Abstract: Considering both non-migrant and migrant couples, this paper studies the effect of cohabiting life partners’ attitudes, resources, and social network compositions on their spouse’s interethnic frie...

Journal ArticleDOI
TL;DR: A framework is introduced for solving the problem of influence maximization, which is based on the member clustering by the K means method, to improve the classification of network users, the data are weighted and the problem is modeled and analyzed as an evolutionary game.
Abstract: Given the importance of maximizing influence in a social network, studies in this field often seek to find the nodes that have the most influence on the social network if designated as primary seeds. In this study, to reduce the complexity of computation algorithms, the problem is divided into several groups that aim to find a group of influential people among users of a social network. In this paper, a framework is introduced for solving the problem of influence maximization, which is based on the member clustering by the K means method, to improve the classification of network users, the data are weighted and the problem is modeled and analyzed as an evolutionary game. Finally, calculate its evolutionary stable strategy. This framework has been tested on real social network data for Abrar University students and we have achieved results such as increasing classification accuracy, reducing error function and finding a stable strategy in the community.