Book chapter · Routledge eBooks · April 22, 2025

Relationship between the linguistic formalisms of web content texts and the real essence of the socially significant event

Orken J. Mamyrbayev, Nina Khairova, Waldemar Wójcik

Abstract

Crime investigation in the Republic of Kazakhstan functions as a cognitive activity with specific legal and procedural characteristics. This activity encompasses the collection, storage, and use of information relevant to investigations, with a focus on identifying, recording, and utilizing crime-related data. Information used by law enforcement is divided into internal and external resources, the latter often containing unstructured data from sources, such as social networks and other public forums. This chapter considers the collection, storage, and use of information relevant to investigations, with a focus on identifying, recording, and utilizing crime-related data. It explores methods for extracting crime-related information from external sources by applying statistical, semantic, and machine learning-based techniques, including text classification, clustering, and latent semantic analysis. The proposed model utilizes a vector space model to identify linguistic markers in crime-related events, highlighting the need for specialized semantic annotation and the development of a criminally related terminology database.

Text and Document Classification TechnologiesComputational and Text Analysis MethodsArtificial Intelligence in Lawcriminal investigationwebsite content analysissocial networks

Relationship between the linguistic formalisms of web content texts and the real essence of the socially significant event

Abstract

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