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Depression tendency detection of Chinese texts in social media data based on Convolutional Neural Networks and Recurrent neural networks.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
2022 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Place, publisher, year, edition, pages
2022.
Keywords [en]
Social media, Recurrent neural network, sentiment analysis, Convolutional Neural Network.
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:bth-22713OAI: oai:DiVA.org:bth-22713DiVA, id: diva2:1642440
Subject / course
DV2572 Master´s Thesis in Computer Science
Educational program
DVADA Master Qualification Plan in Computer Science
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Examiners
Available from: 2022-03-07 Created: 2022-03-07 Last updated: 2022-03-07Bibliographically approved

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Depression tendency detection of Chinese texts in social media data based on Convolutional Neural Networks and Recurrent neural networks.(2156 kB)302 downloads
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File name FULLTEXT02.pdfFile size 2156 kBChecksum SHA-512
eed64ae0a107334782c2f3ede0b6e4953e224a342682d31f576a5200e420e062638cf3c03412ba1c9d61e8b9e827f890752a7ad5051f6f6c06197d448f40872d
Type fulltextMimetype application/pdf

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Xu, KaiweiFei, Yuhang
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CiteExportLink to record
Permanent link

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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
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