Cognitive Social Mining Analysis Using Data Mining Techniques

2019 ◽  
pp. 99-117 ◽  
Author(s):  
Dharmpal Singh
Keyword(s):  
Data Mining ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Statistical Modelling ◽  
Data Interpretation ◽  
Computer Mediated ◽  
The Social ◽  
Using Data ◽  
Collaborative Activities

Social media are based on computer-mediated technologies that smooth the progress of the creation and distribution of information, thoughts, idea, career benefits and other forms of expression via implicit communities and networks. The social network analysis (SNA) has emerged with the increasing popularity of social networking services like Facebook, Twitter, etc. Therefore, information about group cohesion, contribution in activities, and associations among subjects can be obtained from the analysis of the blogs. The analysis of the blogs required well-known knowledge discovery tools to help the administrator to discover participant collaborative activities or patterns with inferences to improve the learning and sharing process. Therefore, the goal of this chapter is to provide the data mining tools for information retrieval, statistical modelling and machine learning to employ data pre-processing, data analysis, and data interpretation processes to support the use of social network analysis (SNA) to improve the collaborative activities for better performance.

Data Mining for Social Network Analysis Using a CLIQUE Algorithm

2019 ◽  
pp. 160-187
Author(s):  
Phu Ngoc Vo ◽  
Tran Vo Thi Ngoc
Keyword(s):  
Data Mining ◽  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
The Social ◽  
The World ◽  
Commercial Applications ◽  
Clique Algorithm

Many different areas of computer science have been developed for many years in the world. Data mining is one of the fields which many algorithms, methods, and models have been built and applied to many commercial applications and research successfully. Many social networks have been invested and developed in the strongest way for the recent years in the world because they have had many big benefits as follows: they have been used by lots of users in the world and they have been applied to many business fields successfully. Thus, a lot of different techniques for the social networks have been generated. Unsurprisingly, the social network analysis is crucial at the present time in the world. To support this process, in this book chapter we have presented many simple concepts about data mining and social networking. In addition, we have also displayed a novel model of the data mining for the social network analysis using a CLIQUE algorithm successfully.

scholarly journals Determining IT Student Profile Using Data Mining and Social Network Analysis

2020 ◽  
Vol 15 (5) ◽  
Author(s):  
Liana Stanca ◽  
Ramona - Lacurezeanu ◽  
Adriana Tiron-Tudor ◽  
Vasile Paul Bresfelean ◽  
Ionut Pandelica
Keyword(s):  
Data Mining ◽  
Labor Market ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Learning And Teaching ◽  
Realistic Description ◽  
University Curricula ◽  
Using Data ◽  
And Behavior

To become higher competitive a university needs to develop a viable students’ absorption strategy on the labor market. A key to the successful development of such a strategy rests to synchronize jobs descriptions with profiles and behavior of IT students. In order to generate this synchronization, it is essential to identify a way to improve university curricula, learning and teaching process based on the students’ profile and on the labor market needs. In this manner, universities could offer IT companies information about their IT students’ profile and behavior. Our paper proposes a data mining and social network analysis to examine IT students’ skills and behavior in order to generate their actual profile. The results contribute to the development of knowledge concerning the IT graduates’ profile and based on this, a solution that might match the university curricula with the labor market requirements. Finally, the results attempt to provide IT companies with information with the aim of better understanding the IT students’ profile and to create a realistic description of the job in the recruitment software on the digital market.

Duality beyondPersons and Groups

2020 ◽  
pp. 391-413
Author(s):  
Sophie Mützel ◽  
Ronald Breiger
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Data ◽  
Future Directions ◽  
Affiliation Networks ◽  
The Social ◽  
Recent Developments ◽  
Principle Of Duality ◽  
Seminal Article

This chapter focuses on the general principle of duality, which was originally introduced by Simmel as the intersection of social circles. In a seminal article, Breiger formalized Simmel’s idea, showing how two-mode types of network data can be transformed into one-mode networks. This formal translation proved to be fundamental for social network analysis, which no longer needed data on who interacted with whom but could work with other types of data. In turn, it also proved fundamental for the analysis of how the social is structured in general, as many relations are dual (e.g. persons and groups, authors and articles, organizations and practices), and are thus susceptible to an analysis according to duality principles. The chapter locates the concept of duality within past and present sociology. It also discusses the use of duality in the analysis of culture as well as in affiliation networks. It closes with recent developments and future directions.

The Oxford Handbook of Social Networks

2020 ◽  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Life ◽  
Information Science ◽  
Computational Social Science ◽  
The Social ◽  
Diverse Field ◽  
The Rich

Social networks fundamentally shape our lives. Networks channel the ways that information, emotions, and diseases flow through populations. Networks reflect differences in power and status in settings ranging from small peer groups to international relations across the globe. Network tools even provide insights into the ways that concepts, ideas and other socially generated contents shape culture and meaning. As such, the rich and diverse field of social network analysis has emerged as a central tool across the social sciences. This Handbook provides an overview of the theory, methods, and substantive contributions of this field. The thirty-three chapters move through the basics of social network analysis aimed at those seeking an introduction to advanced and novel approaches to modeling social networks statistically. The Handbook includes chapters on data collection and visualization, theoretical innovations, links between networks and computational social science, and how social network analysis has contributed substantively across numerous fields. As networks are everywhere in social life, the field is inherently interdisciplinary and this Handbook includes contributions from leading scholars in sociology, archaeology, economics, statistics, and information science among others.

scholarly journals Evaluation of Coordination of Emergency Response Team through the Social Network Analysis. Case Study: Oil and Gas Refinery

2015 ◽  
Vol 6 (1) ◽  
pp. 30-34 ◽  
Author(s):  
Iraj Mohammadfam ◽  
Susan Bastani ◽  
Mahbobeh Esaghi ◽  
Rostam Golmohamadi ◽  
Ali Saee
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Emergency Response ◽  
Oil And Gas ◽  
The Social ◽  
Response Team ◽  
Gas Refinery
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