Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
The article is devoted to the methods of identifying the user's of social networks psychological features and construction on these features user's vulnerabilities profile on the basis of the user's audio preferenses on his personal page in social network VK.com. The description of the software that implements these methods is illustrated in this article. The development of the methodology is based on the generalization of studies that are focused on identifying the correlation between user's musical preferences and his psychological features. The implementation of this method and the results of audio recognition software testing are also described in this article.
Original language | English |
---|---|
Title of host publication | Proceedings of 2017 20th IEEE International Conference on Soft Computing and Measurements, SCM 2017 |
Editors | S. Shaposhnikov |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 90-92 |
Number of pages | 3 |
ISBN (Electronic) | 9781538618103 |
DOIs | |
State | Published - 6 Jul 2017 |
Event | 20th IEEE International Conference on Soft Computing and Measurements, SCM 2017 - St. Petersburg, Russian Federation Duration: 24 May 2017 → 26 May 2017 |
Conference | 20th IEEE International Conference on Soft Computing and Measurements, SCM 2017 |
---|---|
Country/Territory | Russian Federation |
City | St. Petersburg |
Period | 24/05/17 → 26/05/17 |
ID: 36752749