Show HN: I made a neural net that analyzes privacy policies (useguard.com)

Article summary

A neural network has been developed to analyze privacy policies and provide insights into their content. The network is trained on a dataset of labeled privacy policies and can identify potential threats and friendly language. The developer has created a website to showcase the analyzed services and provide information on data breaches and account deletion instructions. The project aims to help users make informed decisions about their online privacy.

Main themes

• privacy policy analysis
• neural network development
• online privacy
• data breaches
• user education

What commenters say

• A scoring system for privacy policies may not be effective as different users have different expectations and concerns.
• A compromise between detailed analysis and simplified scoring could be achieved through adjustable ranking criteria or a pass/fail system.
• Using Google Analytics to track website visitors may be counterintuitive for a privacy-focused project and alternative analytics tools should be considered.
• The development of a privacy policy classifier requires a large and accurate dataset, which can be achieved through transfer learning and collaborative labeling efforts.
• The use of pre-trained language models like ULMFiT can be effective in analyzing privacy policies, but may require substantive changes to the approach.
• Integrating additional features, such as data breach information and account deletion instructions, can enhance the usefulness of the project.
• The project's methodology and data collection process should be transparent and publicly available to ensure credibility and trustworthiness.