A lightweight Pol.is-like.
pip install scikit-learn
python polislite.py
Output
Consensus Statements:
- Climate change requires immediate action (strong agreement)
Divisive Statements:
- Nuclear power is necessary for clean energy
- Carbon tax should be implemented globally
- Individual actions matter for sustainability
- Companies should be held liable for emissions
Group Positions:
Group 1 characteristics:
- strongly agrees with: Climate change requires immediate action
- strongly agrees with: Nuclear power is necessary for clean energy
- strongly disagrees with: Carbon tax should be implemented globally
- strongly disagrees with: Individual actions matter for sustainability
- strongly disagrees with: Companies should be held liable for emissions
Group 2 characteristics:
- strongly agrees with: Climate change requires immediate action
- strongly agrees with: Nuclear power is necessary for clean energy
- strongly agrees with: Carbon tax should be implemented globally
- strongly disagrees with: Individual actions matter for sustainability
- strongly agrees with: Companies should be held liable for emissions
Group 3 characteristics:
- strongly agrees with: Climate change requires immediate action
- strongly disagrees with: Nuclear power is necessary for clean energy
- strongly agrees with: Carbon tax should be implemented globally
- strongly agrees with: Individual actions matter for sustainability
- strongly agrees with: Companies should be held liable for emissions
I focused on small incremental improvements through separation of concerns.
In the branch extract-data-and-output-rendering-to-files, I separated the
data handling and output rendering. Subsequently, in the branch extract-lib,
I isolated the core algorithm into a dedicated library file.
The full changes can be reviewed in the associated pull requests.
I prefer small steps and improving abstraction before focusing more on feature completeness for the algorithm.