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2024 (English)Independent thesis Basic level (professional degree), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

This project proposes the creation of an innovative social media platform, blending key features from other social media platforms with a unique twist. Central to this initiative is an AI-driven system designed to tailor content into specific categories for each user, addressing the challenge of navigating through the vast content on current platforms. This enhances the overall user experience by providing a more structured and engaging way to interact with social media. The approach integrates state-of-the-art OpenAI GPT models and user-centric design principles, aiming to transcend traditional boundaries in social media engagement. The expected outcome is a significant elevation in user satisfaction and the establishment of new benchmarks in digital communication. This project represents a step forward in harmonizing AI technology with user preferences to redefine digital interactions.

Place, publisher, year, edition, pages
2024. , p. 26
Keywords [en]
AI-driven categorization, User-centric design, Real-time profanity filtering, OpenAI GPT models
National Category
Computer Sciences Computer and Information Sciences Communication Systems Computer Systems
Identifiers
URN: urn:nbn:se:hh:diva-54179OAI: oai:DiVA.org:hh-54179DiVA, id: diva2:1880494
Subject / course
Computer science and engineering
Educational program
Computer Engineer, 180 credits
Supervisors
Examiners
Available from: 2024-06-02 Created: 2024-07-01 Last updated: 2025-10-01Bibliographically approved

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Type fulltextMimetype application/pdf

Computer SciencesComputer and Information SciencesCommunication SystemsComputer Systems

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf