Decoding Algorithms for a Sustainable Future: A Bibliometric Analysis of Social Media Studies.
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| Title: | Decoding Algorithms for a Sustainable Future: A Bibliometric Analysis of Social Media Studies. |
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| Authors: | Agrawal, Navya1 agrawalnavya10@gmail.com, Gautam, Arun2 arun.gautam@jecrcu.edu.in |
| Source: | International Journal of Special Education. 2026 Special Issue, Vol. 41, p52-67. 16p. |
| Subject Terms: | *Algorithms, *Social media, *Machine learning, *Artificial intelligence, Sustainability, Big data, Sentiment analysis, Sustainable development |
| Abstract: | This study examines the influence of social media algorithms on through a bibliometric and thematic analysis of recent scholarly literature. The investigation reveals a rapidly growing and highly interdisciplinary research domain that integrates sustainability with advanced digital technologies, particularly artificial intelligence, machine learning and big data analytics. Publication trend shows consistent annual growth, with a sharp rise in output from 2020 onwards and a peak in 2025, indicating that the field has transitioned from a nascent to an expansion phase. Keyword analysis highlights dominant themes such as "sustainability", and "sustainable development," "social media," "algorithms," and "sentiment analysis," underscoring a shift towards algorithmically mediated, data driven approaches to understanding sustainable behavior. The study further identifies that research is concentrated in a few key outlets, characterized by moderate international collaboration, and driven by institutions in Asis and the Middle East, with uneven citation impact across regions. Emerging trends point toward applied, problem solving research on climate change, big data, healthcare, supply chains, and urban system. The findings suggest that social media algorithms are increasingly shaping the visibility, framing and reinforcement of sustainable choices, but also raise concerns about greenwashing, echo chambers and the need for more transparent, ethically designed "sustainable algorithms." The paper concludes by calling for more theory driven, behaviorally grounded research and stronger policy oriented collaboration to harness algorithmic infrastructures for genuine sustainability outcomes rather than merely symbolic or consumerist green behaviors. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Special Education is the property of International Journal of Special Education 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: | Education Research Complete |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 194922796 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Decoding Algorithms for a Sustainable Future: A Bibliometric Analysis of Social Media Studies. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Agrawal%2C+Navya%22">Agrawal, Navya</searchLink><relatesTo>1</relatesTo><i> agrawalnavya10@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Gautam%2C+Arun%22">Gautam, Arun</searchLink><relatesTo>2</relatesTo><i> arun.gautam@jecrcu.edu.in</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Special+Education%22">International Journal of Special Education</searchLink>. 2026 Special Issue, Vol. 41, p52-67. 16p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br />*<searchLink fieldCode="DE" term="%22Social+media%22">Social media</searchLink><br />*<searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br />*<searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Sustainability%22">Sustainability</searchLink><br /><searchLink fieldCode="DE" term="%22Big+data%22">Big data</searchLink><br /><searchLink fieldCode="DE" term="%22Sentiment+analysis%22">Sentiment analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Sustainable+development%22">Sustainable development</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This study examines the influence of social media algorithms on through a bibliometric and thematic analysis of recent scholarly literature. The investigation reveals a rapidly growing and highly interdisciplinary research domain that integrates sustainability with advanced digital technologies, particularly artificial intelligence, machine learning and big data analytics. Publication trend shows consistent annual growth, with a sharp rise in output from 2020 onwards and a peak in 2025, indicating that the field has transitioned from a nascent to an expansion phase. Keyword analysis highlights dominant themes such as "sustainability", and "sustainable development," "social media," "algorithms," and "sentiment analysis," underscoring a shift towards algorithmically mediated, data driven approaches to understanding sustainable behavior. The study further identifies that research is concentrated in a few key outlets, characterized by moderate international collaboration, and driven by institutions in Asis and the Middle East, with uneven citation impact across regions. Emerging trends point toward applied, problem solving research on climate change, big data, healthcare, supply chains, and urban system. The findings suggest that social media algorithms are increasingly shaping the visibility, framing and reinforcement of sustainable choices, but also raise concerns about greenwashing, echo chambers and the need for more transparent, ethically designed "sustainable algorithms." The paper concludes by calling for more theory driven, behaviorally grounded research and stronger policy oriented collaboration to harness algorithmic infrastructures for genuine sustainability outcomes rather than merely symbolic or consumerist green behaviors. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Special Education is the property of International Journal of Special Education 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.) |
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| RecordInfo | BibRecord: BibEntity: Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 16 StartPage: 52 Subjects: – SubjectFull: Algorithms Type: general – SubjectFull: Social media Type: general – SubjectFull: Machine learning Type: general – SubjectFull: Artificial intelligence Type: general – SubjectFull: Sustainability Type: general – SubjectFull: Big data Type: general – SubjectFull: Sentiment analysis Type: general – SubjectFull: Sustainable development Type: general Titles: – TitleFull: Decoding Algorithms for a Sustainable Future: A Bibliometric Analysis of Social Media Studies. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Agrawal, Navya – PersonEntity: Name: NameFull: Gautam, Arun IsPartOfRelationships: – BibEntity: Dates: – D: 07 M: 01 Text: 2026 Special Issue Type: published Y: 2026 Identifiers: – Type: issn-print Value: 08273383 Numbering: – Type: volume Value: 41 Titles: – TitleFull: International Journal of Special Education Type: main |
| ResultId | 1 |
