Irada Y. Alakbarova

Work place: Institute of Information Technology of Azerbaijan National Academy of Sciences 9, B. Vahabzade str., Baku, AZ1141, Azerbaijan

E-mail: airada.09@gmail.com

Website:

Research Interests: Social Information Systems, Data Structures and Algorithms, Analysis of Algorithms

Biography

Irada Y. Alakbarova. She is head of sector at the Institute of Information Technology of ANAS. Her research interests include: Information War, Wiki-technology, Wikimetrics, Data Mining and Social Networks Analysis.

Author Articles
Determining the interests of Social Network Users

By Irada Y. Alakbarova

DOI: https://doi.org/10.5815/ijeme.2023.04.01, Pub. Date: 8 Aug. 2023

The article is devoted to a brief review of approaches to the analysis of social relations in social networks using comments and credentials located in the profiles of social network users. The study aims to determine the interest and behavior of each user. The approach that we propose to determine the interests of social network users requires some methods of machine learning (classification analysis and data clustering). A method based on sentiment analysis and a naive Bayesian classifier is proposed. Determining the interests of social network users based on the intellectual analysis of comments can help to understand the logic of their behavior, and determine social relations between users and problems in society.

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Extraction of Hidden Social Networks from Wiki-Environment Involved in Information Conflict

By Rasim M. Alguliyev Ramiz M. Aliguliyev Irada Y. Alakbarova

DOI: https://doi.org/10.5815/ijisa.2016.02.03, Pub. Date: 8 Feb. 2016

Social network analysis is a widely used technique to analyze relationships among wiki-users in Wikipedia. In this paper the method to identify hidden social networks participating in information conflicts in wiki-environment is proposed. In particular, we describe how text clustering techniques can be used for extraction of hidden social networks of wiki-users caused information conflict. By clustering unstructured text articles caused information conflict we create social network of wiki-users. For clustering of the conflict articles a hybrid weighted fuzzy-c-means method is proposed.

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Other Articles