The social networks' nodes grouping algorithm for the analysis of implicit communities / Perepelitsyn Vasiliy A.,Kravets Alla G. // . - 2016. - V. , l. .

ISSN/EISSN:

2379-3732 / нет данных

Type:

Proceedings Paper

Abstract:

Communication in social networking has become an important part of life for most modern people. Sometimes people do not even think that interacting with other users, as well as sharing their views and interests online, they create a virtual circle of friends, uniting people with similar interests. Information about these user groups is very important, for example in the statistical analysis. The info of this analysis can be used to assist managers in the preparation of social targeting advertising of some new brand to consider the most important groups that may be potentially interested party. This article discusses methods and algorithms for the revealing of such groups - implicit communities. We used natural language processing methods and Page Rank algorithm to develop the methodology. The module has been successfully implemented by SMM team to search potential listeners for Vigel music project among similar style project Amersy.

Author keywords:

social network; groups; group analysis; nodes; graphs; conununities

DOI:

нет данных

Web of Science ID:

ISI:000392155300100

Соавторы в МНС:

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Другие поля

Поле	Значение
Book-Group-Author	IEEE
Booktitle	2016 7TH INTERNATIONAL CONFERENCE ON INFORMATION, INTELLIGENCE, SYSTEMS \& APPLICATIONS (IISA)
Series	International Conference Information Intelligence Systems and Applications
Note	7th International Conference on Information, Intelligence, Systems \& Applications (IISA), Chalkidiki, GREECE, JUL 13-15, 2016
Organization	Inst Elect \& Elect Engineers; BAIF; Univ Piraeus; Aristotle Univ Salonika; Technolog Educ Inst Western Macedonia; BAIF Aristotle Univ Thessaloniki
Publisher	IEEE
Address	345 E 47TH ST, NEW YORK, NY 10017 USA
Language	English
ISBN	978-1-5090-3429-1
Research-Areas	Computer Science; Engineering
Web-of-Science-Categories	Computer Science, Artificial Intelligence; Computer Science, Theory \& Methods; Engineering, Electrical \& Electronic
Author-Email	vasyandler@mail.ru agk@gde.ni
ResearcherID-Numbers	Kravets, Alla/I-2741-2012
ORCID-Numbers	Kravets, Alla/0000-0003-1675-8652
Funding-Acknowledgement	RFBR {[}15-07-06254 A, 16-07-00353 A]
Funding-Text	The reported study was partially supported by RFBR, research project No. 15-07-06254 A, 16-07-00353 A.
Number-of-Cited-References	12
Usage-Count-Last-180-days	1
Usage-Count-Since-2013	2
Doc-Delivery-Number	BG8AT