scholarly journals Know Your Stars Before They Fall Apart: A Social Network Analysis of Telecom Industry to Foster Employee Retention using Data Mining Technique

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Sundus Younis ◽  
Ali Ahsan
Author(s):  
Dharmpal Singh

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.


Author(s):  
Liana Stanca ◽  
Ramona - Lacurezeanu ◽  
Adriana Tiron-Tudor ◽  
Vasile Paul Bresfelean ◽  
Ionut Pandelica

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.


2015 ◽  
Vol 21 (2) ◽  
pp. 95
Author(s):  
Hyo Soung Cha ◽  
Tae Sik Yoon ◽  
Ki Chung Ryu ◽  
Il Won Shin ◽  
Yang Hyo Choe ◽  
...  

2016 ◽  
Vol 139 (6) ◽  
pp. 46-47
Author(s):  
M. Ashrafa ◽  
D. Asha ◽  
D. Radha ◽  
M. Sangeetha ◽  
R. Jayaparvathy

Sign in / Sign up

Export Citation Format

Share Document