Web3.0 Literary Landscape: Deep Learning and Blockchain for Nobel Prize Predictions

Sida Huang*, Jialuoyi Tan, Yuji Dong, Jie Zhang

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

Abstract

This research introduces a cutting-edge Web3 literary analysis platform, harnessing the power of blockchain and deep learning technologies. By employing the immutable and transparent nature of blockchain, the platform ensures robust copyright protection while offering readers enhanced interactive features. It applies deep learning techniques for comprehensive analyses of sentiment, topic, and stylistic elements, which are instrumental in predicting potential Nobel Prize laureates. This methodology not only enhances the accuracy of predictions but also sheds light on the evaluation criteria and historical trends associated with the Nobel Prize. Moreover, the platform adopts a directed graph model alongside the struc2vec algorithm to create text vectors for comparative studies, uncovering similarities between works that have won awards and those that have been nominated. Utilizing the LESS model for detailed content examination, the platform delves into sequence relationships within semantic networks, thus improving interpretability and visualization. The integration of blockchain technology guarantees access to unbiased datasets, enabling more precise literary analyses and predictions. This innovative approach has been validated using works that have either won or been nominated for the Nobel Prize, proving its efficacy in identifying the textual characteristics favored by the Nobel Prize committee.

Original languageEnglish
Title of host publicationICCCN 2024 - 2024 33rd International Conference on Computer Communications and Networks
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350384611
DOIs
Publication statusPublished - 2024
Event33rd International Conference on Computer Communications and Networks, ICCCN 2024 - Big Island, United States
Duration: 29 Jul 202431 Jul 2024

Publication series

NameProceedings - International Conference on Computer Communications and Networks, ICCCN
ISSN (Print)1095-2055

Conference

Conference33rd International Conference on Computer Communications and Networks, ICCCN 2024
Country/TerritoryUnited States
CityBig Island
Period29/07/2431/07/24

Keywords

  • Blockchain
  • Deep learning
  • Semantic analysis
  • Sequence mining
  • struc2vec
  • Web 3.0

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