A review of approaches for topic detection in Twitter.
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| Title: | A review of approaches for topic detection in Twitter. |
|---|---|
| Authors: | Mottaghinia, Zeynab1, z.mottagy@gmail.com, Feizi-Derakhshi, Mohammad-Reza1, Farzinvash, Leili1, Salehpour, Pedram1 |
| Source: | Journal of Experimental & Theoretical Artificial Intelligence; Oct2021, Vol. 33 Issue 5, p747-773, 27p |
| Database: | Applied Science & Technology Source |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 152788735 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=152788735 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/0952813X.2020.1785019 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 27 StartPage: 747 Titles: – TitleFull: A review of approaches for topic detection in Twitter. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Mottaghinia, Zeynab – PersonEntity: Name: NameFull: Feizi-Derakhshi, Mohammad-Reza – PersonEntity: Name: NameFull: Farzinvash, Leili – PersonEntity: Name: NameFull: Salehpour, Pedram IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2021 Type: published Y: 2021 Identifiers: – Type: issn-print Value: 0952813X Numbering: – Type: volume Value: 33 – Type: issue Value: 5 Titles: – TitleFull: Journal of Experimental & Theoretical Artificial Intelligence Type: main |
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