a1

txtlab Multilingual Novels

https://github.com/kin0330/a1

Science Score: 31.0%

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    Found 3 DOI reference(s) in README
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    Low similarity (5.7%) to scientific vocabulary
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txtlab Multilingual Novels

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Metadata Files
Readme Citation

README-Tools and Methods.md

Gender Roles in English Novels (1804-1817): A Literary Analysis

This project will focus on the portrayal of gender roles in English novels, published between 1804 and 1817, to analysis how male and female characters are represented within family settings.

Exsting Research

Robust Quantification of Gender Disparity in Pre-Modern English Literature using Natural Language Processing

  • Author: Mayank Kejriwal, Akarsh Nagaraj

  • DOI: 10.6339/23-JDS1100

A Survey on Gender Bias in Natural Language Processing

  • Author: Karolina Stanczak, Isabelle Augenstein
  • DOI: 10.48550/arXiv.2112.14168

Mitigating Gender Bias in Natural Language Processing: Literature Review

  • Author: Tony Sun, Andrew Gaut, Shirlyn Tang, Yuxin Huang, Mai ElSherief, Jieyu Zhao, Diba Mirza, Elizabeth Belding, Kai-Wei Chang, William Yang Wang
  • DOI: 10.48550/arXiv.1906.08976

Research Question

Do male and female characters in English novels from 1804 to 1817 consistently or differentially appear within family contexts?

Process

This project will employ a quantitative text analysis approach to delve into the 10 novels, with a specific focus on identifying and counting instances of character names and family-related keywords, such as "home," "house," "family" and ect, by encompassing the frequency of these mentions within family settings.

In literary works, when female characters are often linked with words related to the family environment, while male characters are less frequently connected to such terms, it may indicate that the author is highlighting the daily lives of women primarily within the home, as opposed to other settings such as the workplace.

  • Text Data Acquisition

  • Text Analysis

  • Extraction of Male and Female Characters

  • Extraction of Family-Related Vocabulary

  • Frequency Analysis

  • Interpretation

Tools and Methods

To achieve this, I intend to utilize Natural Language Processing (NLP) tools, specifically Python's NLTK library, for text data processing.

Owner

  • Login: kin0330
  • Kind: user

Citation (CITATION)

title: txtlab Multilingual Novels

type: dataset

author: 
  -given name: Piper 
  -family name: Andrew

identifier:
  -type: doi
   value: 10.6084/m9.figshare.2062002.v3
  -url
   value: 'https://doi.org/10.6084/m9.figshare.2062002.v3'

repository-code: 'https://doi.org/10.6084/m9.figshare.2062002.v3'

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