refactor(readme): update project description and badge token

.copier-config.yaml

@@ -24,10 +24,19 @@ package_scripts:
 poe_task_files:
 - .tasks.toml
 - .tasks-extra.toml
-project_description: NLP for Social Science (nlp4ss) is a comprehensive, multilingual course and toolkit designed to bridge the gap between natural language processing (NLP) and social science research. This project provides researchers, students, and practitioners with the knowledge and tools to apply cutting-edge NLP techniques to social science questions. It covers a wide range of topics, including text preprocessing, sentiment analysis, topic modeling, and machine learning applications in social contexts. With interactive Jupyter notebooks, hands-on examples, and real-world case studies, nlp4ss offers a practical approach to integrating computational methods into social science research.
+project_description: NLP for Social Science (nlp4ss) is a comprehensive, multilingual
+    course and toolkit designed to bridge the gap between natural language processing
+    (NLP) and social science research. This project provides researchers, students,
+    and practitioners with the knowledge and tools to apply cutting-edge NLP techniques
+    to social science questions. It covers a wide range of topics, including text
+    preprocessing, sentiment analysis, topic modeling, and machine learning applications
+    in social contexts. With interactive Jupyter notebooks, hands-on examples, and
+    real-world case studies, nlp4ss offers a practical approach to integrating computational
+    methods into social science research.
 project_license: CC-BY-4.0
 project_name: nlp4ss
-project_short_description: A course on applying natural language processing (NLP) techniques for social science research.
+project_short_description: A course on applying natural language processing (NLP)
+    techniques for social science research.
 upload_to_release: true
 upload_to_repository: true
 use_launch_buttons: true

.readthedocs.yaml

@@ -0,0 +1,25 @@
+# .readthedocs.yaml
+# Read the Docs configuration file
+# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
+
+# Required
+version: 2
+
+# Set the version of Python and other tools you might need
+build:
+  os: ubuntu-22.04
+  tools:
+    python: "3.10"
+  jobs:
+    pre_build:
+      # Generate on-the-fly Sphinx configuration from Jupyter Book's _config.yml
+      - "jupyter-book config sphinx book/"
+
+formats:
+  - pdf
+  - epub
+
+# Optionally declare the Python requirements required to build your docs
+python:
+   install:
+   - requirements: book/requirements.txt

CHANGELOG.md

@@ -0,0 +1 @@
+<!--next-version-placeholder-->

README.md

@@ -8,7 +8,7 @@
 [![jupyter-book-image]][docs-url]
 
 <!-- Links: -->
-[codecov-image]: https://codecov.io/gh/entelecheia/nlp4ss/branch/main/graph/badge.svg?token=usYkLC6aBx
+[codecov-image]: https://codecov.io/gh/entelecheia/nlp4ss/branch/main/graph/badge.svg?token=FZ6rvEttdM
 [codecov-url]: https://codecov.io/gh/entelecheia/nlp4ss
 [pypi-image]: https://img.shields.io/pypi/v/nlp4ss
 [license-image]: https://img.shields.io/github/license/entelecheia/nlp4ss
@@ -25,13 +25,13 @@
 [contributing guidelines]: https://github.com/entelecheia/nlp4ss/blob/main/CONTRIBUTING.md
 <!-- Links: -->
 
-Multilingual course creation template with interactive documentation support for international audiences
+A course on applying natural language processing (NLP) techniques for social science research.
 
 - Documentation: [https://nlp4ss.entelecheia.ai][docs-url]
 - GitHub: [https://github.com/entelecheia/nlp4ss][repo-url]
 - PyPI: [https://pypi.org/project/nlp4ss][pypi-url]
 
-This project provides a comprehensive and flexible template for creating and managing multilingual online courses. It leverages GitHub for version control and Jupyter Book for interactive content delivery, enabling educators to easily develop, maintain, and share their educational materials across different languages and cultures.
+NLP for Social Science (nlp4ss) is a comprehensive, multilingual course and toolkit designed to bridge the gap between natural language processing (NLP) and social science research. This project provides researchers, students, and practitioners with the knowledge and tools to apply cutting-edge NLP techniques to social science questions. It covers a wide range of topics, including text preprocessing, sentiment analysis, topic modeling, and machine learning applications in social contexts. With interactive Jupyter notebooks, hands-on examples, and real-world case studies, nlp4ss offers a practical approach to integrating computational methods into social science research.
 
 ## Changelog
 

book/_config.yml

@@ -0,0 +1,103 @@
+#######################################################################################
+# A default configuration that will be loaded for all jupyter books
+# See the documentation for help and more options:
+# https://jupyterbook.org/customize/config.html
+
+#######################################################################################
+# Book settings
+title: "NLP for Social Science" # The title of the book. Will be placed in the left navbar.
+author: "Young Joon Lee" # The author of the book
+copyright: "2024" # Copyright year to be placed in the footer
+# logo: Path to the book logo
+
+# Force re-execution of notebooks on each build.
+# See https://jupyterbook.org/content/execute.html
+execute:
+  execute_notebooks: cache
+  exclude_patterns:
+    - "*.ipynb"
+  allow_errors: true
+
+# Define the name of the latex output file for PDF builds
+latex:
+  latex_documents:
+    targetname: book.tex
+
+# Add a bibtex file so that we can create citations
+bibtex_bibfiles:
+  - references.bib
+
+# Information about where the book exists on the web
+repository:
+  url: https://github.com/entelecheia/nlp4ss # Online location of your book
+  path_to_book: book # Optional path to your book, relative to the repository root
+  branch: main # Which branch of the repository should be used when creating links (optional)
+
+# Add GitHub buttons to your book
+# See https://jupyterbook.org/customize/config.html#add-a-link-to-your-repository
+html:
+  use_issues_button: true
+  use_repository_button: true
+  use_edit_page_button: true
+  favicon: https://assets.entelecheia.ai/favicon.png # favicon: Path to the favicon image
+  google_analytics_id: G-BQJE5V9RK2 # google_analytics_id: Google Analytics ID
+
+sphinx:
+  config:
+    html_extra_path: ["assets"]
+    bibtex_reference_style: author_year
+    mathjax_path: https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js
+    intersphinx_mapping:
+      ebp:
+        - "https://executablebooks.org/en/latest/"
+        - null
+      myst-parser:
+        - "https://myst-parser.readthedocs.io/en/latest/"
+        - null
+      myst-nb:
+        - "https://myst-nb.readthedocs.io/en/latest/"
+        - null
+      sphinx:
+        - "https://www.sphinx-doc.org/en/master"
+        - null
+      nbformat:
+        - "https://nbformat.readthedocs.io/en/latest"
+        - null
+      sd:
+        - "https://sphinx-design.readthedocs.io/en/latest"
+        - null
+      sphinxproof:
+        - "https://sphinx-proof.readthedocs.io/en/latest/"
+        - null
+    hoverxref_intersphinx:
+      - "sphinxproof"
+    mathjax3_config:
+      tex:
+        macros:
+          "N": "\\mathbb{N}"
+          "floor": ["\\lfloor#1\\rfloor", 1]
+          "bmat": ["\\left[\\begin{array}"]
+          "emat": ["\\end{array}\\right]"]
+    add_module_names: false
+    autosummary_generate: true
+
+  extra_extensions:
+    - sphinx.ext.intersphinx
+    - sphinx.ext.autodoc
+    - sphinx.ext.autosummary
+    - sphinx.ext.napoleon
+    - sphinx.ext.viewcode
+    - sphinx_inline_tabs
+    - sphinx_proof
+    - sphinx_examples
+    - hoverxref.extension
+    - sphinxcontrib.youtube
+    - sphinxcontrib.video
+    - sphinxcontrib.mermaid
+    - sphinx_thebe
+    - sphinx_carousel.carousel
+    - sphinxcontrib.lastupdate
+
+launch_buttons:
+  colab_url: "https://colab.research.google.com"
+  thebe: true

book/en/index.md

@@ -10,7 +10,7 @@
 <!-- Links: -->
 [hyperfast python template]: https://github.com/entelecheia/hyperfast-python-template
 
-[codecov-image]: https://codecov.io/gh/entelecheia/nlp4ss/branch/main/graph/badge.svg?token=usYkLC6aBx
+[codecov-image]: https://codecov.io/gh/entelecheia/nlp4ss/branch/main/graph/badge.svg?token=FZ6rvEttdM
 [codecov-url]: https://codecov.io/gh/entelecheia/nlp4ss
 [pypi-image]: https://img.shields.io/pypi/v/nlp4ss
 [license-image]: https://img.shields.io/github/license/entelecheia/nlp4ss
@@ -27,13 +27,13 @@
 [contributing guidelines]: https://github.com/entelecheia/nlp4ss/blob/main/CONTRIBUTING.md
 <!-- Links: -->
 
-Multilingual course creation template with interactive documentation support for international audiences
+A course on applying natural language processing (NLP) techniques for social science research.
 
 - Documentation: [https://nlp4ss.entelecheia.ai][docs-url]
 - GitHub: [https://github.com/entelecheia/nlp4ss][repo-url]
 - PyPI: [https://pypi.org/project/nlp4ss][pypi-url]
 
-This project provides a comprehensive and flexible template for creating and managing multilingual online courses. It leverages GitHub for version control and Jupyter Book for interactive content delivery, enabling educators to easily develop, maintain, and share their educational materials across different languages and cultures.
+NLP for Social Science (nlp4ss) is a comprehensive, multilingual course and toolkit designed to bridge the gap between natural language processing (NLP) and social science research. This project provides researchers, students, and practitioners with the knowledge and tools to apply cutting-edge NLP techniques to social science questions. It covers a wide range of topics, including text preprocessing, sentiment analysis, topic modeling, and machine learning applications in social contexts. With interactive Jupyter notebooks, hands-on examples, and real-world case studies, nlp4ss offers a practical approach to integrating computational methods into social science research.
 
 ## Changelog
 

book/ko/index.md

@@ -10,7 +10,7 @@
 <!-- Links: -->
 [hyperfast python template]: https://github.com/entelecheia/hyperfast-python-template
 
-[codecov-image]: https://codecov.io/gh/entelecheia/nlp4ss/branch/main/graph/badge.svg?token=usYkLC6aBx
+[codecov-image]: https://codecov.io/gh/entelecheia/nlp4ss/branch/main/graph/badge.svg?token=FZ6rvEttdM
 [codecov-url]: https://codecov.io/gh/entelecheia/nlp4ss
 [pypi-image]: https://img.shields.io/pypi/v/nlp4ss
 [license-image]: https://img.shields.io/github/license/entelecheia/nlp4ss
@@ -27,13 +27,13 @@
 [contributing guidelines]: https://github.com/entelecheia/nlp4ss/blob/main/CONTRIBUTING.md
 <!-- Links: -->
 
-Multilingual course creation template with interactive documentation support for international audiences
+A course on applying natural language processing (NLP) techniques for social science research.
 
 - Documentation: [https://nlp4ss.entelecheia.ai][docs-url]
 - GitHub: [https://github.com/entelecheia/nlp4ss][repo-url]
 - PyPI: [https://pypi.org/project/nlp4ss][pypi-url]
 
-This project provides a comprehensive and flexible template for creating and managing multilingual online courses. It leverages GitHub for version control and Jupyter Book for interactive content delivery, enabling educators to easily develop, maintain, and share their educational materials across different languages and cultures.
+NLP for Social Science (nlp4ss) is a comprehensive, multilingual course and toolkit designed to bridge the gap between natural language processing (NLP) and social science research. This project provides researchers, students, and practitioners with the knowledge and tools to apply cutting-edge NLP techniques to social science questions. It covers a wide range of topics, including text preprocessing, sentiment analysis, topic modeling, and machine learning applications in social contexts. With interactive Jupyter notebooks, hands-on examples, and real-world case studies, nlp4ss offers a practical approach to integrating computational methods into social science research.
 
 ## Changelog