Abstract

The article discusses the growing need to analyze and understand web user behavior due to the unprecedented amount of digital content being generated and distributed on the Internet. Web content intelligence is presented as an effective way to explore and extract valuable information from online content, including websites, social media platforms, and other digital sources, to better understand web users' interests, preferences, and behaviors. The ability to identify web users based on their online behavior is important for industries such as marketing, psychology, and law enforcement. However, there are certain problems associated with this approach, such as ensuring the privacy and security of web users’ data, as well as assessing the accuracy and reliability of web content analysis tools. The purpose of the article is to review the current state of web content analysis, its potential applications in various industries, and its role in shaping the digital future. The article emphasizes the importance of an interdisciplinary approach to the study of virtual identification and self-presentation in online communities, taking into account the socio-demographic characteristics of a web personality involved in social interactions. The article also explores the latest trends and developments in the field of web data mining, including web content analysis, web structure analysis, web page usage analysis, and social media data analysis. A software solution for conducting intelligent analysis of web content is proposed to form a social and digital identity of a web user using a specialized dictionary of content markers of a web community member.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call