Mining Social Network Data for Predictive Personality Modelling by Employing Machine Learning Techniques

2019 ◽  
pp. 113-127 ◽  
Author(s):  
Arjun Sengupta ◽  
Anupam Ghosh
Keyword(s):  
Machine Learning ◽  
Social Network ◽  
Machine Learning Techniques ◽  
Network Data ◽  
Social Network Data ◽  
Learning Techniques

scholarly journals Depression detection from social network data using machine learning techniques

2018 ◽  
Vol 6 (1) ◽  
Author(s):  
Md. Rafiqul Islam ◽  
Muhammad Ashad Kabir ◽  
Ashir Ahmed ◽  
Abu Raihan M. Kamal ◽  
Hua Wang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Social Network ◽  
Machine Learning Techniques ◽  
Network Data ◽  
Social Network Data ◽  
Learning Techniques ◽  
Depression Detection

In-Network Data Aggregation for Information-Centric WSNs using Unsupervised Machine Learning Techniques

2021 ◽  
Author(s):  
Marcelo E. Pellenz ◽  
Rosana Lachowski ◽  
Edgard Jamhour ◽  
Glauber Brante ◽  
Guilherme Luiz Moritz ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Aggregation ◽  
Machine Learning Techniques ◽  
Network Data ◽  
Unsupervised Machine Learning ◽  
Learning Techniques

scholarly journals Social Network Modelling using tools of Statistical Mechanics

2020 ◽  
Author(s):  
Ashish Menon ◽  
Nithin K Rajendran ◽  
Anish Chandrachud
Keyword(s):  
Machine Learning ◽  
Social Network ◽  
Phase Space ◽  
Statistical Mechanics ◽  
Disease Transmission ◽  
Machine Learning Techniques ◽  
Network Modelling ◽  
Business Partnership ◽  
Learning Techniques ◽  
Statistical Mechanism

The objective of this paper is to study a treatment to social network analysis using the principles of statistical mechanics. After revisiting the popular models and random graph frameworks of complex networks, a formalism to statistical mechanism based on the conventional concepts like phase space, interactions and ensembles is devised. Specific machine learning techniques are employed for the purpose of figuring out the relevant phase-space equations. Thereafter, specific applications of the formalism is explored in the context of business partnership optimization and disease transmission. Several analogues with the statistical mechanics treatment of thermodynamics have also been made.

scholarly journals Detecting Private Information in Large Social Network using mixed Machine Learning Techniques

2019 ◽  
Author(s):  
Pasquale De Luca
Keyword(s):  
Machine Learning ◽  
Social Network ◽  
Mobile Phones ◽  
Private Information ◽  
Current Problem ◽  
Personal Information ◽  
Private Life ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
The Web

The violation of privacy, others people or personal, is a very current problem, which concerns not only on the web but also in private life. In the years 1990 it was expected that nowadays, that any routine operation was carried out "manually", and it would be performed through mobile phones or personal computers. The problem pertains the distribution network that allows to share and bring together information and as result the network becomes unsafe, if subjected to attacks. Nowaday we put personal information on web because otherwise we are seen as “weak”. This work aims to measure and analyze how much information are shared by users of a pre-established social network and it is carried out through a set of algorithms techniques of machine learning.

Sign in / Sign up

Export Citation Format

Share Document