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Xing Wang, Shouhua Zhang, and Ivan Smetannikov. 2020. Fiction Popularity Prediction Based on Emotion Analysis. In 2020 International Conference on Control, Robotics and Intelligent System (CCRIS 2020). Association for Computing Machinery, New York, NY, USA, 169–175. DOI:https://doi.org/10.1145/3437802.3437831

Fiction popularity prediction based on emotion analysis

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Author: Wang, Xing1; Zhang, Shouhua2; Smetannikov, Ivan3
Organizations: 1ITMO University Saint Petersburg, Russia
2University of Oulu, Oulu, Finland
3Machine Learning lab ITMO University Saint Petersburg, Russia
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.7 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe202101262673
Language: English
Published: Association for Computing Machinery, 2020
Publish Date: 2021-01-26
Description:

Abstract

In addition to bringing us knowledge, books also bring us emotional experiences. How do the emotional fluctuations brought by books affect readers’ evaluation of them? What is the difference in emotional fluctuations between books of different popularity? In this paper, we model and analyse the emotional fluctuations of different fiction books with different popularity and study the feasibility of predicting the popularity of fiction books using emotional fluctuations and recurrent neural networks. A new dataset is also generated to support this research and other related researches. Our proposed method obtained the best accuracy of 73.4% for predicting the popularity of fiction books and 41.4% for predicting genres. Some interesting data insights are also extracted from the dataset.

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ISBN Print: 978-1-4503-8805-4
Pages: 169 - 175
DOI: 10.1145/3437802.3437831
OADOI: https://oadoi.org/10.1145/3437802.3437831
Host publication: CCRIS 2020: 2020 International Conference on Control, Robotics and Intelligent System
Conference: International Conference on Control, Robotics and Intelligent System
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
213 Electronic, automation and communications engineering, electronics
Subjects:
Emotion Analysis
Natural Language Processing
Popularity Prediction
Article
Funding: This research received valuable help from Shouhua Zhang of University of Oulu, Oulu, Finland. This work is financially supported by the Government of the Russian Federation, grant 08-08.
Copyright information: © 2020 Copyright held by the owner/author(s). Publication rights licensed to ACM. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in CCRIS 2020: 2020 International Conference on Control, Robotics and Intelligent System, https://doi.org/10.1145/3437802.3437831.