An AI-driven approach to measure corporate and CEO reputation using Aspect-Based Sentiment Analysis on news articles
Project description
Repdex
An AI-driven approach to measure corporate and CEO reputation using Aspect-Based Sentiment Analysis on news articles
- Documentation: https://repdex.entelecheia.ai
- GitHub: https://github.com/entelecheia/repdex
- PyPI: https://pypi.org/project/repdex
Repdex is an innovative project that leverages advanced language models like GPT-4o, Claude 3.5, or Llama 3.1 through LangChain to perform Aspect-Based Sentiment Analysis (ABSA) on news articles. It aims to quantify and analyze the reputation of companies and their CEOs, providing valuable insights for corporate communications teams, investors, analysts, and researchers.
Changelog
See the CHANGELOG for more information.
Contributing
Contributions are welcome! Please see the contributing guidelines for more information.
License
This project is released under the MIT License.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file repdex-0.1.0.tar.gz
.
File metadata
- Download URL: repdex-0.1.0.tar.gz
- Upload date:
- Size: 3.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.8.0 pkginfo/1.11.1 readme-renderer/44.0 requests/2.32.3 requests-toolbelt/1.0.0 urllib3/2.2.3 tqdm/4.66.5 importlib-metadata/8.5.0 keyring/25.4.1 rfc3986/2.0.0 colorama/0.4.6 CPython/3.10.12
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 72f30bf66fc178d82ff939c89eeb354a11ab23a5463256302e0d543be5e8aeb8 |
|
MD5 | 52c9dae10105ab934d1e5b56ecb07c04 |
|
BLAKE2b-256 | 07df1be7f8c5c6c32ad1c2a35617e64d1cf6558fb650ee0caebb1cacdf610166 |
File details
Details for the file repdex-0.1.0-py3-none-any.whl
.
File metadata
- Download URL: repdex-0.1.0-py3-none-any.whl
- Upload date:
- Size: 4.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.8.0 pkginfo/1.11.1 readme-renderer/44.0 requests/2.32.3 requests-toolbelt/1.0.0 urllib3/2.2.3 tqdm/4.66.5 importlib-metadata/8.5.0 keyring/25.4.1 rfc3986/2.0.0 colorama/0.4.6 CPython/3.10.12
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 068c7efa909ed5c07e5cac0d00c2ee1e171070a983b5cffa0336917d3f2cd57f |
|
MD5 | 7d9d876f518638a008a93ebd0f70fa14 |
|
BLAKE2b-256 | 5615832d05ce72c1199ac0c537a9dcf95f65fa90c566e4b1cb8d6196693214df |