СИСТЕМА АВТОМАТИЗОВАНОГО АНАЛІЗУ ЦИФРОВОГО СЛІДУ КОРИСТУВАЧА В СОЦІАЛЬНИХ МЕДІА З ВИКОРИСТАННЯМ OSINT
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| Title: | СИСТЕМА АВТОМАТИЗОВАНОГО АНАЛІЗУ ЦИФРОВОГО СЛІДУ КОРИСТУВАЧА В СОЦІАЛЬНИХ МЕДІА З ВИКОРИСТАННЯМ OSINT |
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| Alternate Title: | SYSTEM FOR AUTOMATED ANALYSIS OF USER DIGITAL FOOTPRINT IN SOCIAL MEDIA USING OSINT. |
| Authors: | Власова, А. В.1, Назаров, В. О.1, Ярова, І. А.1, Кушніренко, Н. І.1 kushnirenko@op.edu.ua |
| Source: | Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì. 2025, Vol. 15 Issue 4, p536-544. 9p. |
| Subjects: | Digital footprint, Open source intelligence, Computer user identification, Acquisition of data, Ukrainian language, Information retrieval, Algorithms, Social media |
| Geographic Terms: | Ukraine |
| Abstract: | The article presents a system for automated analysis of user digital footprint in social media using Open Source Intelligence (OSINT) approaches adapted for the Ukrainian language. Growing user activity on social networks creates privacy risks through accumulation of personal information. The aim of the work is to create a specialized system for comprehensive analysis of user digital presence in Telegram and YouTube considering morphological features of Ukrainian language and cultural context. Analysis of existing social platform research methods revealed limitations when processing Ukrainian content, particularly insufficient recognition accuracy and absence of specialized linguistic models. The proposed system consists of three sequential algorithms: a data collection algorithm through Telegram and YouTube APIs, a comprehensive text content analysis algorithm using TF-IDF method for key term extraction and langdetect library for automatic language detection, and an integrated profile construction algorithm with heterogeneous data normalization based on textual, social, temporal, and behavioral components. Experimental validation on a sample of 100 users across different age categories demonstrated system accuracy of 73% for Ukrainian content with average processing time of 85-95 seconds per user. The highest accuracy was achieved in determining temporal activity patterns (87%) and social activity level (77%). Scientific novelty lies in creating a specialized system for Ukrainian language considering its morphological features, including integration of TF-IDF frequency analysis methods adapted for word forms specificity, development of Ukrainian internet slang dictionary with over 800 entries, and construction of a comprehensive digital profile model based on four components. [ABSTRACT FROM AUTHOR] |
| Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 190880290 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: СИСТЕМА АВТОМАТИЗОВАНОГО АНАЛІЗУ ЦИФРОВОГО СЛІДУ КОРИСТУВАЧА В СОЦІАЛЬНИХ МЕДІА З ВИКОРИСТАННЯМ OSINT – Name: TitleAlt Label: Alternate Title Group: TiAlt Data: SYSTEM FOR AUTOMATED ANALYSIS OF USER DIGITAL FOOTPRINT IN SOCIAL MEDIA USING OSINT. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Власова%2C+А%2E+В%2E%22">Власова, А. В.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Назаров%2C+В%2E+О%2E%22">Назаров, В. О.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Ярова%2C+І%2E+А%2E%22">Ярова, І. А.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Кушніренко%2C+Н%2E+І%2E%22">Кушніренко, Н. І.</searchLink><relatesTo>1</relatesTo><i> kushnirenko@op.edu.ua</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Informatics+%26+Mathematical+Methods+in+Simulation+%2F+Informatika+ta+Matematičnì+Metodi+v+Modelûvannì%22">Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì</searchLink>. 2025, Vol. 15 Issue 4, p536-544. 9p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Digital+footprint%22">Digital footprint</searchLink><br /><searchLink fieldCode="DE" term="%22Open+source+intelligence%22">Open source intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+user+identification%22">Computer user identification</searchLink><br /><searchLink fieldCode="DE" term="%22Acquisition+of+data%22">Acquisition of data</searchLink><br /><searchLink fieldCode="DE" term="%22Ukrainian+language%22">Ukrainian language</searchLink><br /><searchLink fieldCode="DE" term="%22Information+retrieval%22">Information retrieval</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Social+media%22">Social media</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Ukraine%22">Ukraine</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The article presents a system for automated analysis of user digital footprint in social media using Open Source Intelligence (OSINT) approaches adapted for the Ukrainian language. Growing user activity on social networks creates privacy risks through accumulation of personal information. The aim of the work is to create a specialized system for comprehensive analysis of user digital presence in Telegram and YouTube considering morphological features of Ukrainian language and cultural context. Analysis of existing social platform research methods revealed limitations when processing Ukrainian content, particularly insufficient recognition accuracy and absence of specialized linguistic models. The proposed system consists of three sequential algorithms: a data collection algorithm through Telegram and YouTube APIs, a comprehensive text content analysis algorithm using TF-IDF method for key term extraction and langdetect library for automatic language detection, and an integrated profile construction algorithm with heterogeneous data normalization based on textual, social, temporal, and behavioral components. Experimental validation on a sample of 100 users across different age categories demonstrated system accuracy of 73% for Ukrainian content with average processing time of 85-95 seconds per user. The highest accuracy was achieved in determining temporal activity patterns (87%) and social activity level (77%). Scientific novelty lies in creating a specialized system for Ukrainian language considering its morphological features, including integration of TF-IDF frequency analysis methods adapted for word forms specificity, development of Ukrainian internet slang dictionary with over 800 entries, and construction of a comprehensive digital profile model based on four components. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=190880290 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.15276/imms.v15.no4.536 Languages: – Code: ukr Text: Ukrainian PhysicalDescription: Pagination: PageCount: 9 StartPage: 536 Subjects: – SubjectFull: Digital footprint Type: general – SubjectFull: Open source intelligence Type: general – SubjectFull: Computer user identification Type: general – SubjectFull: Acquisition of data Type: general – SubjectFull: Ukrainian language Type: general – SubjectFull: Information retrieval Type: general – SubjectFull: Algorithms Type: general – SubjectFull: Social media Type: general – SubjectFull: Ukraine Type: general Titles: – TitleFull: СИСТЕМА АВТОМАТИЗОВАНОГО АНАЛІЗУ ЦИФРОВОГО СЛІДУ КОРИСТУВАЧА В СОЦІАЛЬНИХ МЕДІА З ВИКОРИСТАННЯМ OSINT Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Власова, А. В. – PersonEntity: Name: NameFull: Назаров, В. О. – PersonEntity: Name: NameFull: Ярова, І. А. – PersonEntity: Name: NameFull: Кушніренко, Н. І. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: 2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 22235744 Numbering: – Type: volume Value: 15 – Type: issue Value: 4 Titles: – TitleFull: Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì Type: main |
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