10.46243/jst.2023.v8.i07.pp124-132 registered
Suspicious Account Detection Using Machine Learning Techniques
Resolves to https://www.jst.org.in/index.php/pub/article/view/739
Held by Longman Publishers (India) · prefix 10.46243 live · DOI address https://doi.org/10.46243/jst.2023.v8.i07.pp124-132
Registered 29 Sep 2026 via crossref · record version 2 · last change 30 Sep 2026, 12:00 AM · record sha256 fcc8ca0af2837af7…
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What the DOI identifies
JournalArticle — an article in a journal · Digital · Visual · en
Suspicious Account Detection Using Machine Learning Techniques (PrincipalTitle)
Published 2023
Part of Journal of Science & Technology · ISSN 2456-5660 · volume 08 · issue 07 · pages 124–132
Agents
- Anjum Afshan (author)
- B.Anvesh kumar (author)
- Dr.V.Bapuji (author)
- Longman Publishers (publisher)
Identifiers DOI 10.46243/jst.2023.v8.i07.pp124-132
Abstract
In the current generation, social networking sites have become an integral part of life for most people. On social networking sites such as Facebook, Instagram, and Twitter, thousands of people create their profiles daily, interacting with each based on the classification for detecting Suspicious accounts on social networks. Here the traditionally way has been used for different classification methods in this paper. The implementation of machine learning and natural language processor (NLP) techniques are done to enhance the accuracy of others regardless of location and time. Our goal is to understand who encourages threats in social networking profiles. To determine which social network profiles are genuine and which ones are Suspicious profiles, The support vector machine (SVM) and Naves bays algorithm technique can also be applied to achieve this strategy.
System metadata — ISO 26324:2025, Annex B · DOI Handbook 10.1
Each element by the standard's name (Annex B: reference elements, then administrative) and the Handbook's (in grey), read off the record above.
| Element | Value | In the record |
|---|---|---|
| DOI Name DOI name | 10.46243/jst.2023.v8.i07.pp124-132 | doi |
| Referent Type referentType | Creation | referent |
| Referent Sub-Type referentSubType | JournalArticle — an article in a journal | type |
| Referent Name(s) referentName(s) | Suspicious Account Detection Using Machine Learning Techniques (PrincipalTitle, en) | titles |
| Basic Metadata basicMetadata | author: Anjum Afshan author: B.Anvesh kumar author: Dr.V.Bapuji publisher: Longman Publishers published: 2023 part of: Journal of Science & Technology · ISSN 2456-5660 · vol. 08 · no. 07 · pp. 124–132 language: en form: Digital · Visual · Language | agents, dates, container, language, structural_type, modes, characters |
| Referent Identifier(s) alternateIdentifier(s) | none besides the DOI | identifiers, relations (IsSameAs) |
| Registration Authority registrationAuthorityCode | Crossref — issued by Crossref (member 25296); held here as a copy | record.source_agency (our code, ra_doi_name, for names issued here once appointed) |
| Created Date issueDate | 2026-09-23 | record.registered (when the DOI name was first registered) |
| relatedIdentifiers | none needed — the descriptive metadata is in this record | container, relations (only where the descriptive metadata lives at another identifier) |
complete Every System Metadata element is here, with the basic metadata a journal article needs.
The System Metadata Declaration (JSON) · the Kernel Metadata Declaration (XML) · what each sub-type needs
History — the ledger
Every change to this DOI, in order, as it was recorded. Entries are only ever added, never changed or removed.
| # | When | What | By | Changes |
|---|---|---|---|---|
| 1 | 29 Sep 2026, 10:00 PM | register registered at Crossref; record read from api.crossref.org | Administrator (admin) | 86 fields set · sha256 b393b27b9f5c… |
| 2 | 30 Sep 2026, 12:00 AM | update record re-read from api.crossref.org | Administrator (admin) | container.titles.0.value: |
Machine-readable: the history as JSON, with the full record after each change.
