scholarly journals Novel Node Centrality-Based Efficient Empirical Robustness Assessment for Directed Network

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Xiaolong Deng ◽  
Hao Ding ◽  
Yong Chen ◽  
Cai Chen ◽  
Tiejun Lv
Keyword(s):  
Social Network ◽  
Vulnerability Assessment ◽  
Online Social Networks ◽  
Information Transfer ◽  
Large Scale ◽  
Real Life ◽  
Clustering Coefficient ◽  
Network Robustness ◽  
Directed Network ◽  
Online Social Media

In recent years, while extensive researches on various networks properties have been proposed and accomplished, little has been proposed and done on network robustness and node vulnerability assessment under cascades in directed large-scale online community networks. In essential, an online directed social network is a group-centered and information spread-dominated online platform which is very different from the traditional undirected social network. Some further research studies have indicated that the online social network has high robustness to random removals of nodes but fails to the intentional attacks, particularly to those attacks based on node betweenness or node directed coefficient. To explore on the robustness of directed social network, in this article, we have proposed two novel node centralities of ITG (information transfer gain-based probability clustering coefficient) and I M p v (directed path-based node importance centrality). These two new centrality models are designed to capture this cascading effect in directed online social networks. Furthermore, we also propose a new and highly efficient computing method based on iterations for I M p v . Then, with the abundant experiments on the synthetic signed network and real-life networks derived from directed online social media and directed human mobile phone calling network, it has been proved that our ITG and I M p v based on directed social network robustness and node vulnerability assessment method is more accurate, efficient, and faster than several traditional centrality methods such as degree and betweenness. And we also have proposed the solid reasoning and proof process of iteration times k in computation of I M p v . To the best knowledge of us, our research has drawn some new light on the leading edge of robustness on the directed social network.

A Novel Spatio-Temporal Access Control Model for Online Social Networks and Visual Verification

2021 ◽  
Vol 11 (2) ◽  
pp. 17-31
Author(s):  
Lanfang Zhang ◽  
Zhiyong Zhang ◽  
Ting Zhao
Keyword(s):  
Social Network ◽  
Access Control ◽  
Online Social Networks ◽  
Online Social Network ◽  
Rapid Development ◽  
Real Life ◽  
Control Model ◽  
Mobile Internet ◽  
Access Control Model ◽  
Spatio Temporal

With the rapid development of mobile internet, a large number of online social networking platforms and tools have been widely applied. As a classic method for protecting the privacy and information security of social users, access control technology is evolving with the spatio-temporal change of social application requirements and scenarios. However, nowadays there is a lack of effective theoretical model of social spatio-temporal access control as a guide. This paper proposed a novel spatio-temporal access control model for online social network (STAC) and its visual verification, combined with the advantages of discretionary access control, using formal language to describe the access control rules based on spatio-temporal, and real-life scenarios for access control policy description, realizes a more fine-grained access control mechanism for social network. By using the access control verification tool ACPT developed by NIST to visually verify the proposed model, the security and effectiveness of the STAC model are proved.

Prediction of Social Influence for Provenance of Misinformation in Online Social Network Using Big Data Approach

2020 ◽  
Author(s):  
Kumaran P ◽  
Rajeswari Sridhar
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Law Enforcement ◽  
Online Social Networks ◽  
Large Scale ◽  
Online Social Network ◽  
Root Cause ◽  
Minimum Number ◽  
Targeted Marketing ◽  
Implicit And Explicit

Abstract Online social networks (OSNs) is a platform that plays an essential role in identifying misinformation like false rumors, insults, pranks, hoaxes, spear phishing and computational propaganda in a better way. Detection of misinformation finds its applications in areas such as law enforcement to pinpoint culprits who spread rumors to harm the society, targeted marketing in e-commerce to identify the user who originates dissatisfaction messages about products or services that harm an organizations reputation. The process of identifying and detecting misinformation is very crucial in complex social networks. As misinformation in social network is identified by designing and placing the monitors, computing the minimum number of monitors for detecting misinformation is a very trivial work in the complex social network. The proposed approach determines the top suspected sources of misinformation using a tweet polarity-based ranking system in tandem with sarcasm detection (both implicit and explicit sarcasm) with optimization approaches on large-scale incomplete network. The algorithm subsequently uses this determined feature to place the minimum set of monitors in the network for detecting misinformation. The proposed work focuses on the timely detection of misinformation by limiting the distance between the suspected sources and the monitors. The proposed work also determines the root cause of misinformation (provenance) by using a combination of network-based and content-based approaches. The proposed work is compared with the state-of-art work and has observed that the proposed algorithm produces better results than existing methods.

A novel genetic algorithm-based improvement model for online communities and trust networks

2021 ◽  
Vol 40 (1) ◽  
pp. 1597-1608
Author(s):  
Ilker Bekmezci ◽  
Murat Ermis ◽  
Egemen Berki Cimen
Keyword(s):  
Genetic Algorithm ◽  
Social Networks ◽  
Social Network ◽  
Online Communities ◽  
Real Life ◽  
Statistical Properties ◽  
Clustering Coefficient ◽  
Data Sets ◽  
Life Data ◽  
Real Life Data

Social network analysis offers an understanding of our modern world, and it affords the ability to represent, analyze and even simulate complex structures. While an unweighted model can be used for online communities, trust or friendship networks should be analyzed with weighted models. To analyze social networks, it is essential to produce realistic social models. However, there are serious differences between social network models and real-life data in terms of their fundamental statistical parameters. In this paper, a genetic algorithm (GA)-based social network improvement method is proposed to produce social networks more similar to real-life data sets. First, it creates a social model based on existing studies in the literature, and then it improves the model with the proposed GA-based approach based on the similarity of the average degree, the k-nearest neighbor, the clustering coefficient, degree distribution and link overlap. This study can be used to model the structural and statistical properties of large-scale societies more realistically. The performance results show that our approach can reduce the dissimilarity between the created social networks and the real-life data sets in terms of their primary statistical properties. It has been shown that the proposed GA-based approach can be used effectively not only in unweighted networks but also in weighted networks.

Working Adults' Buying Intention Through Online Social Network

2021 ◽  
Vol 17 (4) ◽  
pp. 92-116
Author(s):  
Syed Shah Alam ◽  
Chieh-Yu Lin ◽  
Mohd Helmi Ali ◽  
Nor Asiah Omar ◽  
Mohammad Masukujjaman
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Online Social Networks ◽  
Perceived Risk ◽  
Word Of Mouth ◽  
Online Social Network ◽  
Perceived Value ◽  
Online Social Media ◽  
Starting Point

Most businesses have online social media presence; therefore, understanding of working adult's perception on buying through online social networks is vital. The aim of this study is to examine the effect of perceived value, sociability, usability, perceived risk, trust, and e-word-of-mouth on buying intention through online social network sites. The research model for this study was developed based on the literature on information system research. This study adopted convenient sampling of non-probability sampling procedure. Data were collected through self-administered questionnaire, and PLS-based path analysis was used to analyse responses. The findings of the study shows that perceived value, sociability, usability, e-word-of-mouth, attitude, and subjective norm are significant constructs of buying intention through online social networks. This research can serve as a starting point for online shopping research through online social media while encouraging further exploration and integration addition adoption constructs.

scholarly journals Online Social Networks (OSN) Evolution Model Based on Homophily and Preferential Attachment

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 654 ◽  
Author(s):  
Jebran Khan ◽  
Sungchang Lee
Keyword(s):  
Social Networks ◽  
Structural Properties ◽  
Online Social Networks ◽  
Large Scale ◽  
Preferential Attachment ◽  
Real Life ◽  
Synthetic Data ◽  
Evolution Model ◽  
Scale Invariant ◽  
Scale Free

In this paper, we propose a new scale-free social networks (SNs) evolution model that is based on homophily combined with preferential attachments. Our model enables the SN researchers to generate SN synthetic data for the evaluation of multi-facet SN models that are dependent on users’ attributes and similarities. Homophily is one of the key factors for interactive relationship formation in SN. The synthetic graph generated by our model is scale-invariant and has symmetric relationships. The model is dynamic and sustainable to changes in input parameters, such as number of nodes and nodes’ attributes, by conserving its structural properties. Simulation and evaluation of models for large-scale SN applications need large datasets. One way to get SN data is to generate synthetic data by using SN evolution models. Various SN evolution models are proposed to approximate the real-life SN graphs in previous research. These models are based on SN structural properties such as preferential attachment. The data generated by these models is suitable to evaluate SN models that are structure dependent but not suitable to evaluate models which depend on the SN users’ attributes and similarities. In our proposed model, users’ attributes and similarities are utilized to synthesize SN graphs. We evaluated the resultant synthetic graph by analyzing its structural properties. In addition, we validated our model by comparing its measures with the publicly available real-life SN datasets and previous SN evolution models. Simulation results show our resultant graph to be a close representation of real-life SN graphs with users’ attributes.

scholarly journals The Use of Mobile Phones for the Prevention and Control of Arboviral Diseases: A Scoping Review

2020 ◽  
Author(s):  
Maria Angelica Carrillo ◽  
Axel Kroeger ◽  
Rocio Cardenas Sanchez ◽  
Sonia Diaz Monsalve ◽  
Silvia Runge Ranzinger
Keyword(s):  
Mobile Phone ◽  
Mobile Phones ◽  
Scoping Review ◽  
Information Transfer ◽  
Large Scale ◽  
Grey Literature ◽  
Real Life ◽  
Rapid Expansion ◽  
Health Concern ◽  
Arboviral Diseases

Abstract Background: The rapid expansion of dengue, Zika and chikungunya with large scale outbreaks are an increasing public health concern in many countries. Additionally, the recent coronavirus pandemic urged the need to get connected for fast information transfer and exchange. As response, health programmes have -among other interventions- incorporated digital tools such as mobile phones for supporting the control and prevention of infectious diseases. However, little is known about the benefits of mobile phone technology in terms of input, process and outcome dimensions. The purpose of this scoping review is to analyse the evidence of the use of mobile phones as an intervention tool regarding the performance, acceptance, usability, feasibility, cost and effectiveness in dengue, Zika and chikungunya control programmes. Methods: We conducted a scoping review of studies and reports by systematically searching: i) electronic databases (PubMed, PLOS ONE, PLOS Neglected Tropical Disease, LILACS, WHOLIS, ScienceDirect and Google scholar), ii) grey literature, using Google web and iii) documents in the list of references of the selected papers. Selected studies were categorized using a pre-determined data extraction form. Finally, a narrative summary of the evidence related to general characteristics of available mobile health tools and outcomes was produced. Results: The systematic literature search identified 1289 records, 32 of which met the inclusion criteria. From the reference lists of included articles 4 records were identified coming to a total of 36 studies. The content analysis identified five mobile phone categories: mobile applications (n = 18), short message services (n=7), camera phone (n = 6), mobile phone tracking data (n = 4), and simple mobile communication (n = 1). These devices were used for surveillance, prevention and management. In general, mobile phone-based studies reported good performance, acceptance by users, usability in downloads as well as feasibility of mobile phone under real life conditions and effectiveness in terms of contributing to a reduction of vectors and disease. It can be concluded that there are great opportunities for using mobile phones in the fight against arboviral diseases as well as other epidemic diseases . Further studies particularly on acceptance, cost and effectiveness at scale are recommended.

scholarly journals The use of mobile phones for the prevention and control of arboviral diseases: a scoping review

2020 ◽  
Author(s):  
Maria Angelica Carrillo ◽  
Axel Kroeger ◽  
Rocio Cardenas Sanchez ◽  
Sonia Diaz Monsalve ◽  
Silvia Runge Ranzinger
Keyword(s):  
Mobile Phone ◽  
Mobile Phones ◽  
Scoping Review ◽  
Information Transfer ◽  
Large Scale ◽  
Grey Literature ◽  
Real Life ◽  
Rapid Expansion ◽  
Health Concern ◽  
Arboviral Diseases

Abstract Background: The rapid expansion of dengue, Zika and chikungunya with large scale outbreaks are an increasing public health concern in many countries. Additionally, the recent coronavirus pandemic urged the need to get connected for fast information transfer and exchange. As response, health programmes have -among other interventions- incorporated digital tools such as mobile phones for supporting the control and prevention of infectious diseases. However, little is known about the benefits of mobile phone technology in terms of input, process and outcome dimensions. The purpose of this scoping review is to analyse the evidence of the use of mobile phones as an intervention tool regarding the performance, acceptance, usability, feasibility, cost and effectiveness in dengue, Zika and chikungunya control programmes.Methods: We conducted a scoping review of studies and reports by systematically searching: i) electronic databases (PubMed, PLOS ONE, PLOS Neglected Tropical Disease, LILACS, WHOLIS, ScienceDirect and Google scholar), ii) grey literature, using Google web and iii) documents in the list of references of the selected papers. Selected studies were categorized using a pre-determined data extraction form. Finally, a narrative summary of the evidence related to general characteristics of available mobile health tools and outcomes was produced.Results: The systematic literature search identified 1289 records, 32 of which met the inclusion criteria and 4 records from the reference lists. A total of 36 studies were included coming from twenty different countries. Five mobile phone services were identified in this review: mobile applications (n = 18), short message services (n=7), camera phone (n = 6), mobile phone tracking data (n = 4), and simple mobile communication (n = 1). Mobile phones were used for surveillance, prevention, diagnosis, and communication demonstrating good performance, acceptance and usability by users, as well as feasibility of mobile phone under real life conditions and effectiveness in terms of contributing to a reduction of vectors/ disease and improving users-oriented behaviour changes. It can be concluded that there are benefits for using mobile phones in the fight against arboviral diseases as well as other epidemic diseases. Further studies particularly on acceptance, cost and effectiveness at scale are recommended.

scholarly journals Detection of Harassment Type of Cyberbullying: A Dictionary of Approach Words and Its Impact

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Syed Mahbub ◽  
Eric Pardede ◽  
A. S. M. Kayes
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Intellectual Development ◽  
Positive Impact ◽  
Real Life ◽  
Machine Learning Algorithms ◽  
Online Bullying ◽  
Predatory Behaviour ◽  
The Difference

The purpose of this paper is to analyse the effects of predatory approach words in the detection of cyberbullying and to propose a mechanism of generating a dictionary of such approach words. The research incorporates analysis of chat logs from convicted felons, to generate a dictionary of sexual approach words. By analysing data across multiple social networks, the study demonstrates the usefulness of such a dictionary of approach words in detection of online predatory behaviour through machine learning algorithms. It also shows the difference between the nature of contents across specific social network platforms. The proposed solution to detect cyberbullying and the domain of approach words are scalable to fit real-life social media, which can have a positive impact on the overall health of online social networks. Different types of cyberbullying have different characteristics. However, existing cyberbullying detection works are not targeted towards any of these specific types. This research is tailored to focus on sexual harassment type of cyberbullying and proposes a novel dictionary of approach words. Since cyberbullying is a growing threat to the mental health and intellectual development of adolescents in the society, models targeted towards the detection of specific type of online bullying or predation should be encouraged among social network researchers.

A novel method for identifying influential nodes in complex networks based on multiple attributes

2018 ◽  
Vol 32 (28) ◽  
pp. 1850307 ◽  
Author(s):  
Dong Liu ◽  
Hao Nie ◽  
Baowen Zhang
Keyword(s):  
Large Scale ◽  
Real Life ◽  
Entropy Method ◽  
Viral Marketing ◽  
Clustering Coefficient ◽  
Node Location ◽  
Influential Nodes ◽  
Multiple Attributes ◽  
Comparison Algorithms ◽  
Large Scale Networks

Identifying influential nodes is a crucial issue in epidemic spreading, controlling the propagation process of information and viral marketing. Thus, algorithms for exploring vital nodes have aroused more and more concern among researchers. Recently, scholars have proposed various types of algorithms based on different perspectives. However, each of these methods has their own strengths and weaknesses. In this work, we introduce a novel multiple attributes centrality for identifying significant nodes based on the node location and neighbor information attributes. We call our proposed method the MAC. Specifically, we utilize the information of the number of iterations per node to enhance the accuracy of the K-shell algorithm, so that the location attribute can be used to distinguish the important nodes more deeply. And the neighbor information attribute we selected can effectively avoid the overlapping problem of neighbor information propagation caused by large clustering coefficient of networks. Because these two indexes have different emphases, we use entropy method to assign them reasonable weights. In addition, MAC has low time complexity O(n), which makes the algorithm suitable for large-scale networks. In order to objectively assess its performance, we utilize the Susceptible-Infected-Recovered (SIR) model to verify the propagation capability of each node and compare the MAC method with several classic methods in six real-life datasets. Extensive experiments verify the superiority of our algorithm to other comparison algorithms.

scholarly journals The Use of Mobile Phones for the Prevention and Control of Arboviral Diseases: A Scoping Review

2020 ◽  
Author(s):  
Maria Angelica Carrillo ◽  
Axel Kroeger ◽  
Rocio Cardenas Sanchez ◽  
Sonia Diaz Monsalve ◽  
Silvia Runge Ranzinger
Keyword(s):  
Mobile Phone ◽  
Mobile Phones ◽  
Scoping Review ◽  
Information Transfer ◽  
Large Scale ◽  
Grey Literature ◽  
Real Life ◽  
Rapid Expansion ◽  
Health Concern ◽  
Arboviral Diseases

Abstract Background: The rapid expansion of dengue, Zika and chikungunya with large scale outbreaks are an increasing public health concern in many countries. Additionally, the recent coronavirus pandemic urged the need to get connected for fast information transfer and exchange. As response, health programmes have -among other interventions- incorporated digital tools such as mobile phones for supporting the control and prevention of infectious diseases. However, little is known about the benefits of mobile phone technology in terms of input, process and outcome dimensions. The purpose of this scoping review is to analyse the evidence of the use of mobile phones as an intervention tool regarding the performance, acceptance, usability, feasibility, cost and effectiveness in dengue, Zika and chikungunya control programmes.Methods: We conducted a scoping review of studies and reports by systematically searching: i) electronic databases (PubMed, PLOS ONE, PLOS Neglected Tropical Disease, LILACS, WHOLIS, ScienceDirect and Google scholar), ii) grey literature, using Google web and iii) documents in the list of references of the selected papers. Selected studies were categorized using a pre-determined data extraction form. Finally, a narrative summary of the evidence related to general characteristics of available mobile health tools and outcomes was produced. Results: The systematic literature search identified 1289 records, 32 of which met the inclusion criteria and 4 records from the reference lists. A total of 36 studies were included coming from twenty different countries. Five mobile phone services were identified in this review: mobile applications (n = 18), short message services (n=7), camera phone (n = 6), mobile phone tracking data (n = 4), and simple mobile communication (n = 1). Mobile phones were used for surveillance, prevention, diagnosis, and communication demonstrating good performance, acceptance and usability by users, as well as feasibility of mobile phone under real life conditions and effectiveness in terms of contributing to a reduction of vectors/ disease and improving users-oriented behaviour changes. It can be concluded that there are great opportunities for using mobile phones in the fight against arboviral diseases as well as other epidemic diseases. Further studies particularly on acceptance, cost and effectiveness at scale are recommended.

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