Near consensus complex linear and nonlinear social networks

2014 ◽  
Vol 28 (13) ◽  
pp. 1450106 ◽  
Author(s):  
Bingo Wing-Kuen Ling ◽  
Charlotte Yuk-Fan Ho ◽  
Lidong Wang ◽  
Kok-Lay Teo ◽  
Chi K. Tse ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Steady State ◽  
Optimization Problem ◽  
Threshold Value ◽  
Weight Matrix ◽  
Initial State ◽  
Complex Linear ◽  
Definition Of ◽  
The Given

Some of the nodes of complex social networks may support for a given proposal, while the rest of the nodes may be against the given proposal. Even though all the nodes support for or are against the given proposal, the decision certitudes of individual nodes may be different. In this case, the steady state values of the decision certitudes of the majority of the nodes are either higher than or lower than a threshold value. Deriving the near consensus property is a key to the analysis of the behaviors of complex social networks. So far, no result on the behaviors of the complex social networks satisfying the near consensus property has been reported. Hence, it is useful to extend the definition of the exact consensus property to that of a near consensus property and investigate the behaviors of the complex social networks satisfying the near consensus property. This paper extends the definition of exact consensus complex social networks to that of near consensus complex social networks. For complex linear social networks, this paper investigates the relationships among the vectors representing the steady state values of the decision certitudes of the nodes, the influence weight matrix and the set of vectors representing the initial state values of the decision certitudes of the nodes under a given near consensus specification. The above analysis is based on the Eigen theory. For complex nonlinear social networks with certain types of nonlinearities, the relationship between the influence weight matrix and the vectors representing the steady state values of the decision certitudes of the nodes is studied. When a complex nonlinear social network does not achieve the exact consensus property, the optimal near consensus condition that the complex social network can achieve is derived. This problem is formulated as an optimization problem. The total number of nodes that the decision certitudes of the nodes are either higher than or lower than a threshold value is maximized subject to the corresponding near consensus specification. The optimization problem is a nonsmooth optimization problem. The nonsmooth constraints are first approximated by smooth constraints. Then, the approximated optimization problem is solved via a conventional smooth optimization approach. Computer numerical simulation results as well as the comparisons of the behaviors of complex nonlinear social networks to those of the complex linear social networks are presented. The obtained results demonstrate that some complex social networks can satisfy the near consensus property but not the exact consensus property. Also, the conditions for the near consensus property are dependent on the types of nonlinearities, the influence weight matrix and the vectors representing the initial state values of the decision certitudes of the nodes.

scholarly journals Determining the proximity of groups in social networks based on text analysis using big data

2019 ◽  
pp. 521-526
Author(s):  
A S Mukhin ◽  
I A Rytsarev ◽  
R A Paringer ◽  
A V Kupriyanov ◽  
D V Kirsh
Keyword(s):  
Social Networks ◽  
Big Data ◽  
Social Network ◽  
Data Collection ◽  
Text Analysis ◽  
Software Tool ◽  
Text Data ◽  
The Social ◽  
Information Research ◽  
Definition Of

The article is devoted to the definition of such groups in social networks. The object of the study was selected data social network Vk. Text data was collected, processed and analyzed. To solve the problem of obtaining the necessary information, research was conducted in the field of optimization of data collection of the social network Vk. A software tool that provides the collection and subsequent processing of the necessary data from the specified resources has been developed. The existing algorithms of text analysis, mainly of large volume, were investigated and applied.

scholarly journals Social Networks and Transnational Social Fields: A Review of Quantitative and Mixed-Methods Approaches

2018 ◽  
Vol 54 (1) ◽  
pp. 177-204 ◽  
Author(s):  
Miranda Jessica Lubbers ◽  
Ashton M. Verdery ◽  
José Luis Molina
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Mixed Methods ◽  
Social Fields ◽  
Transnational Social Fields ◽  
Small Set ◽  
Individual Household ◽  
Place Of Origin ◽  
Definition Of ◽  
Transnational Social Networks

Scholars of transnationalism have argued that migrants create transnational social fields or spaces that connect their place of origin to destination areas. Despite the centrality that social networks have in the definition of these concepts, quantitative and mixed-methods social network research is rare in research on transnationalism. This situation, however, has changed over the last decade, and the transnational social networks of migrants have been studied with multiple methodologies. So far, this literature has not been systematically evaluated. With the aim of taking stock of this research, we classify the literature into four types of approaches (individual, household, dyad/small set, and community) and review their distinct contributions regarding the functioning of immigrants’ transnational networks, as well as the relative strengths and limitations of each approach. On the basis of our analysis, we discuss pathways for future investigation.

scholarly journals Correlation between Triadic Closure and Homophily Formed over Location-Based Social Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Nauman Ali Khan ◽  
Wuyang Zhou ◽  
Mudassar Ali Khan ◽  
Ahmad Almogren ◽  
Ikram Ud Din
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Research Direction ◽  
Social Actors ◽  
The Social ◽  
Depth Analysis ◽  
Location Based Social Network ◽  
Triadic Closure ◽  
Location Based Social Networks ◽  
The Given

Social Internet of Things (SIoT) is a variation of social networks that adopt the property of peer-to-peer networks, in which connections between the things and social actors are automatically established. SIoT is a part of various organizations that inherit the social interaction, and these organizations include industries, institutions, and other establishments. Triadic closure and homophily are the most commonly used measures to investigate social networks’ formation and nature, where both measures are used exclusively or with statistical models. The triadic closure patterns are mapped for actors’ communication behavior over a location-based social network, affecting the homophily. In this study, we investigate triads emergence in homophilic social networks. This evaluation is based on the empirical review of triads within social networks (SNs) formed on Big Data. We utilized a large location-based dataset for an in-depth analysis, the Chinese telecommunication-based anonymized call detail records (CDRs). Two other openly available datasets, Brightkite and Gowalla, were also studied. We identified and proposed three social triad classes in a homophilic network to feature the correlation between social triads and homophily. The study opened a promising research direction that relates the variation of homophily based on closure triads nature. The homophilic triads are further categorized into transitive and intransitive groups. As our concluding research objective, we examined the relative triadic throughput within a location-based social network for the given datasets. The research study attains significant results highlighting the positive connection between homophily and a specific social triad class.

scholarly journals Election Control in Social Networks via Edge Addition or Removal

2020 ◽  
Vol 34 (02) ◽  
pp. 1878-1885
Author(s):  
Matteo Castiglioni ◽  
Diodato Ferraioli ◽  
Nicola Gatti
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Positive Result ◽  
Optimization Problem ◽  
Optimal Solution ◽  
The Social ◽  
Wide Range ◽  
Local Modification ◽  
Edge Addition ◽  
Over Time

We focus on the scenario in which messages pro and/or against one or multiple candidates are spread through a social network in order to affect the votes of the receivers. Several results are known in the literature when the manipulator can make seeding by buying influencers. In this paper, instead, we assume the set of influencers and their messages to be given, and we ask whether a manipulator (e.g., the platform) can alter the outcome of the election by adding or removing edges in the social network. We study a wide range of cases distinguishing for the number of candidates or for the kind of messages spread over the network. We provide a positive result, showing that, except for trivial cases, manipulation is not affordable, the optimization problem being hard even if the manipulator has an unlimited budget (i.e., he can add or remove as many edges as desired). Furthermore, we prove that our hardness results still hold in a reoptimization variant, where the manipulator already knows an optimal solution to the problem and needs to compute a new solution once a local modification occurs (e.g., in bandit scenarios where estimations related to random variables change over time).

Analysis of Social Network Mutate in Start-Up Enterprises Evolution

2011 ◽  
Vol 181-182 ◽  
pp. 9-13
Author(s):  
Min Wang ◽  
Hua Tao Peng
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Environmental Changes ◽  
Network Evolution ◽  
Reverse Direction ◽  
Start Up ◽  
Mutation Theory ◽  
Basic Concepts ◽  
Definition Of ◽  
Social Network Evolution

In the process of evolution in Start-up Enterprises, its social networks will often occurred Mutations phenomenon because of environmental changes, the changing conditions, the reverse direction, management of error, etc. This paper analyzed the evolution in social network of Start-up Enterprises through the basic concepts of the theory of mutations, definition of mutations in Start-up Enterprises′ social network evolution, and the using of swallow-tail mutation theory; proposed countermeasures of how to make full use of social network to facilitate Start-up Enterprises timely and accurately identify mutations, take measures, reduce the loss which mutations brought.

BMADSN: Big data multi-community anomaly detection in social networks

2019 ◽  
pp. 002072091989106 ◽  
Author(s):  
Manjunatha HC ◽  
Mohanasundaram R
Keyword(s):  
Social Networks ◽  
Big Data ◽  
Social Network ◽  
Anomaly Detection ◽  
Research Area ◽  
Detection Techniques ◽  
Graph Metrics ◽  
The People ◽  
Illegal Activities ◽  
The Given

In today's world, most of the people are using social networks for day-to-day activities. The most frequently used social sites are Facebook, Twitter, Google+, etc. These popular social networks are used by some of the users for abnormal or illegal activities. It is very important and necessary to identify and avoid such illegal activities without harming anyone in the society. In recent decades, social networks are becoming a popular research area for most researchers. Many authors are doing research on social network datasets and proposing various anomaly detection mechanisms to identify anomalous activities in both static and dynamic growing social networks. Various anomaly detection techniques are proposed by the authors to investigate malicious activities in social networks. In general, the process of identifying anomaly activities of the users in the given dataset is called anomaly detection. The anomaly detection in social networks is the process of investigating whether the users of the given social networks are involved in illegal activities or not. In this work, we proposed a most elegant approach to identify the anomalous or outlier users in the given social network. The proposed approach is considering the users participated in multiple communities of social networks. The designed algorithms are implemented and tested in a big data environment three node cluster using open source Hadoop ecosystem tools. Algorithm1 is used to investigate the nodes/users who participated in multiple communities of the given social network’s dataset. Algorithm2 takes the set of users participated in multiple communities and apply graph metrics such as degree and community score to predict the users involved in the anomalous activity.

scholarly journals SOCIAL NETWORKS IN THE CONTEXT OF SOCIAL CAPITAL: A REVIEW OF FOREIGN THEORETICAL APPROACHES

2020 ◽  
Vol 3 (3) ◽  
pp. 146-166
Author(s):  
Darya A. Lastovkina
Keyword(s):  
Social Capital ◽  
Social Networks ◽  
Social Network ◽  
Social System ◽  
Structural Element ◽  
Theoretical Approaches ◽  
Communication Space ◽  
Characteristic Features ◽  
Developing Area ◽  
Definition Of

Currently, society lives in the conditions of continuous expansion of the communication space. This is manifested in the transformation of old and the emergence of new types of interaction of individuals in the economic, political, social, spiritual spheres of society. The study of social networks is an actively developing area in theoretical sociology, and the concept of social networks is the most natural in the description and construction of a social structure. In a broad sense, a social network is understood as many points (members of a social system), to a greater or lesser extent, related to each other. In this article we will illustrate the main stages of the evolution of the concept of “social network” in the works of foreign researchers. Let's take a closer look at foreign theoretic approaches to the study of social networks as a structural element of social capital. In the conclusion of our analysis, we will list the main characteristic features of a social network, on the basis of which we will formulate a generalized definition of this phenomenon.

The role of social networking in the life of under-age persons with special needs

Servis plus ◽  
10.12737/5533 ◽  
2014 ◽  
Vol 8 (3) ◽  
pp. 16-21
Author(s):  
Артур Михеев ◽  
Artur Mikheev
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Networking ◽  
Special Needs ◽  
Major Element ◽  
Social Adaptation ◽  
User Needs ◽  
The Social ◽  
Definition Of

The article present the results of research into the role of social networking in the life of under-age (aged 10–18) people with special needs (the number of respondents —120 under-age people). The aim of the research is to identify the degree of influence that social networks have on the process of social adaptation of under-age people with special needs. Each of the social networks under scrutiny was analyzed as to the user opportunities it has to offer and the user needs it can satisfy. The author also provides a definition of (1) the concept of a social network, (2) a social graph as a major element of a social network, (3) a person with special needs, and (4) population disability.

Unveiling Network Data Patterns in Social Media

2022 ◽  
pp. 571-588
Author(s):  
Maria Prosperina Vitale ◽  
Maria Carmela Catone ◽  
Ilaria Primerano ◽  
Giuseppe Giordano
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Data ◽  
Online Data ◽  
Complex Picture ◽  
Definition Of ◽  
Network Patterns

The present study focuses on the usefulness of social network analysis in unveiling network patterns in social media. Specifically, the propagation and consumption of information on Twitter through network analysis tools are investigated to discover the presence of specific conversational patterns in the derived online data. The choosing of Twitter is motivated by the fact that it induces the definition of relationships between users by following communication flows on specific topics of interest and identifying key profiles who influence debates in the digital space. Further lines of research are discussed regarding the tools for discovering the spread of fake news. Considerable disinformation can be generated on social networks, offering a complex picture of informational disorientation in the digital society.

EFFECTIVENESS OF OPINION INFLUENCE APPROACHES IN HIGHLY CLUSTERED ONLINE SOCIAL NETWORKS

2014 ◽  
Vol 17 (02) ◽  
pp. 1450008
Author(s):  
MELISSA FALETRA ◽  
NATHAN PALMER ◽  
JEFFREY S. MARSHALL
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Online Social Network ◽  
Threshold Value ◽  
Clustering Coefficient ◽  
Scale Free ◽  
Small Influence ◽  
Online Advertisement ◽  
The Difference

A mathematical model was developed for opinion propagation on online social networks using a scale-free network with an adjustable clustering coefficient. Connected nodes influence each other when the difference between their opinion values is less than a threshold value. The model is used to examine effectiveness of three different approaches for influencing public opinion. The approaches examined include (1) a "Class", defined as an approach (such as a class or book) that greatly influences a small, randomly selected portion of the population, (2) an "Advertisement", defined as an approach (such as a TV or online advertisement) that has a small influence at each viewing on a large randomly selected portion of the population, and (3) an "App", defined as an approach (such as a Facebook game or smartphone "App") that spreads via the online social network (rather than randomly) and has a small influence at each viewing on the affected population. The Class and Advertisement approaches result in similar overall influence on the population, despite the fact that these approaches are highly different. In contrast, the App approach has a much more significant effect on opinion values of users occupying clusters within the social network compared to the overall population.

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