scholarly journals blockmodeling: an R package for Generalized Blockmodeling

2021 ◽  
Author(s):  
Miha Matjašič ◽  
Marjan Cugmas ◽  
Aleš Žiberna
Keyword(s):  
Social Networks ◽  
R Package ◽  
Interval Scale ◽  
Theoretical Foundations ◽  
Analysis Of Social Networks

This paper presents the R package blockmodeling which is primarily meant as an implementation of generalized blockmodeling (more broadly blockmodeling) for valued networks where the values of the ties are assumed to be measured on at least interval scale. Blockmodeling is one of the most commonly used approaches in the analysis of (social) networks, which deals with the analysis of relationships or connections, between the units studied (e.g., peoples, organizations, journals etc.). The R package blockmodeling implements several approaches for the generalized blockmodeling of binary and valued networks. Generalized blockmodeling is commonly used to cluster nodes in a network with regard to the structure of their links. The theoretical foundations of generalized blockmodeling for binary and valued networks are summarized in the paper while the use of the R package blockmodeling is illustrated by applying it to an empirical dataset.

scholarly journals blockmodeling

2020 ◽  
Vol 17 (2) ◽  
Author(s):  
Miha Matjašič ◽  
Marjan Cugmas ◽  
Aleš Žiberna
Keyword(s):  
Social Networks ◽  
R Package ◽  
Interval Scale ◽  
Theoretical Foundations ◽  
Analysis Of Social Networks

This paper presents the R package blockmodeling which is primarily meant as an implementation of generalized blockmodeling (more broadly blockmodeling) for valued networks where the values of the ties are assumed to be measured on at least interval scale. Blockmodeling is one of the most commonly used approaches in the analysis of (social) networks, which deals with the analysis of relationships or connections, between the units studied (e.g., peoples, organizations, journals etc.). The R package blockmodeling implements several approaches for the generalized blockmodeling of binary and valued networks. Generalized blockmodeling is commonly used to cluster nodes in a network with regard to the structure of their links. The theoretical foundations of generalized blockmodeling for binary and valued networks are summarized in the paper while the use of the R package blockmodeling is illustrated by applying it to an empirical dataset.

Conducting Psychological Examinations for Citizens in Possession of Weapons: Strengthening State Control Over Circulation of Weapons

2021 ◽  
Vol 8 (2) ◽  
pp. 87-94
Author(s):  
Sergey N. Bokov ◽  
Maxim I. Zhdanov
Keyword(s):  
Social Networks ◽  
Specific Form ◽  
Personality Questionnaire ◽  
State Control ◽  
Gun Ownership ◽  
Frustration Tolerance ◽  
Psychological Analysis ◽  
Psychological Examination ◽  
The Subject ◽  
Analysis Of Social Networks

In the article, in connection with the introduction of amendments to the federal legislation, specific issues regarding the conducting of a psychological survey of citizens gun owners and candidates for gun ownership are considered. A battery of psychodiagnostic techniques that can be used in the course of a psychological examination (progressive matrices of J. Raven, a questionnaire of the Level of subjective control, and a method for diagnosing frustration tolerance from Rosenzweig, Minnesota Multidisciplinary Personality Questionnaire) is proposed and justified, as is an algorithm for conducting psychodiagnostic research. Furthermore, a proposal to include in the psychological examination, a psychological analysis of social networks (provided that the subject is a member of their group) has been made. The possible participation in the psychological survey gun owners and candidates for gun ownership psychologists of Rosgvardiya are justified and the specific form of their participation in the survey is indicated.

A Review of Machine Learning and Data Mining Approaches for Business Applications in Social Networks

2013 ◽  
Vol 9 (1) ◽  
pp. 36-53
Author(s):  
Evis Trandafili ◽  
Marenglen Biba
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Social Networks ◽  
Large Scale ◽  
Viral Marketing ◽  
Social Network Mining ◽  
Business Applications ◽  
Mining Community ◽  
Recent Developments ◽  
Analysis Of Social Networks

Social networks have an outstanding marketing value and developing data mining methods for viral marketing is a hot topic in the research community. However, most social networks remain impossible to be fully analyzed and understood due to prohibiting sizes and the incapability of traditional machine learning and data mining approaches to deal with the new dimension in the learning process related to the large-scale environment where the data are produced. On one hand, the birth and evolution of such networks has posed outstanding challenges for the learning and mining community, and on the other has opened the possibility for very powerful business applications. However, little understanding exists regarding these business applications and the potential of social network mining to boost marketing. This paper presents a review of the most important state-of-the-art approaches in the machine learning and data mining community regarding analysis of social networks and their business applications. The authors review the problems related to social networks and describe the recent developments in the area discussing important achievements in the analysis of social networks and outlining future work. The focus of the review in not only on the technical aspects of the learning and mining approaches applied to social networks but also on the business potentials of such methods.

Token Salaries and Social Answers in Work Relations in Africa

1999 ◽  
Vol 4 (2) ◽  
pp. 15-24
Author(s):  
Massimo Repetti
Keyword(s):  
Social Networks ◽  
Urban Space ◽  
Daily Routine ◽  
Work Relations ◽  
The Social ◽  
The Gift ◽  
Strength Of Weak Ties ◽  
Popular Economy ◽  
Client Relations ◽  
Analysis Of Social Networks

In Dakar, faced with crisis and uncertainty, social answers begin to appear. Only those having a supportive social network could find a place in the labour's market. The observation of the daily routine of any of Dakarís micro-businesses and its social aspects, reveals the wide area of interference that exists between waged worker and the relation networks with family and relatives, ethnic groups and Muslim brotherhoods. The urban economy is supported by a network of family, alliance, and client relations. The overlap existing between waged and unwaged work can be understood only by looking closely at the network of social ties present outside the production site. Switching from the analysis of urban work relationships in Africa to the analysis of social networks is almost spontaneous, because a system of relational actions and strategies grows around the figure of the worker. The importance of the “strength of weak ties” in procuring employment is as a whole confirmed, but African sociability creates an intense inter-network relational interchange. Dakarís urban space feeds a “popular economy” where social networks and the gift-giving logic co-exist with market economy. This economy utilise different wage embryos or tokens salaries for each of the social players.

Similarity-based link prediction in social networks: A path and node combined approach

2016 ◽  
Vol 43 (5) ◽  
pp. 683-695 ◽  
Author(s):  
Chuanming Yu ◽  
Xiaoli Zhao ◽  
Lu An ◽  
Xia Lin
Keyword(s):  
Social Networks ◽  
Link Prediction ◽  
Computational Analysis ◽  
Rapid Development ◽  
Area Under The Curve ◽  
Combined Approach ◽  
Topological Features ◽  
Different Types ◽  
Path Dependent ◽  
Analysis Of Social Networks

With the rapid development of the Internet, the computational analysis of social networks has grown to be a salient issue. Various research analyses social network topics, and a considerable amount of attention has been devoted to the issue of link prediction. Link prediction aims to predict the interactions that might occur between two entities in the network. To this aim, this study proposed a novel path and node combined approach and constructed a methodology for measuring node similarities. The method was illustrated with five real datasets obtained from different types of social networks. An extensive comparison of the proposed method against existing link prediction algorithms was performed to demonstrate that the path and node combined approach achieved much higher mean average precision (MAP) and area under the curve (AUC) values than those that only consider common nodes (e.g. Common Neighbours and Adamic/Adar) or paths (e.g. Random Walk with Restart and FriendLink). The results imply that two nodes are more likely to establish a link if they have more common neighbours of lower degrees. The weight of the path connecting two nodes is inversely proportional to the product of degrees of nodes on the pathway. The combination of node and topological features can substantially improve the performance of similarity-based link prediction, compared with node-dependent and path-dependent approaches. The experiments also demonstrate that the path-dependent approaches outperform the node-dependent appraoches. This indicates that topological features of networks may contribute more to improving performance than node features.

Network Visualization

2020 ◽  
pp. 195-212
Keyword(s):  
Social Networks ◽  
Visual Inspection ◽  
Exploratory Analysis ◽  
Basic Theory ◽  
Network Visualization ◽  
Research Focus ◽  
Analysis Of Social Networks

Visual inspection of networks is a powerful tool in exploratory analysis of social networks. However, visualization of graphs has inherent problems that may result in misleading visualizations. This chapter first introduces basic theory behind these inherent problems. Then it introduces features of common layout algorithms used in visualization. Through applied examples, the chapter explores the use of layout parameters to obtain visualizations appropriate for the research focus.

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