Hacker News Historical Headlines Review, Analysis, and Push Workflow
This workflow can automatically fetch the top news headlines from the Hacker News homepage for a specified date, utilize a large language model for intelligent categorization and trend analysis, generate themed Markdown news summaries, and push them to subscribed users via a Telegram channel. It addresses the issues of historical news data aggregation and information overload, helping users quickly grasp technological trends and hot topics. It is suitable for technology media, researchers, and information service providers, enhancing the timeliness and value of the content.
Workflow Name
Hacker News Historical Headlines Review, Analysis, and Push Workflow
Key Features and Highlights
This workflow automatically scrapes the front-page headlines of Hacker News for specified dates spanning multiple years. It leverages the Google Gemini large language model to intelligently categorize, distill, and analyze trends from years of headlines. The output is a thematically organized news summary in Markdown format, which is then automatically pushed to subscribers via a Telegram channel.
Highlights include:
- Cross-year comparison of technology news on the same calendar day
- Intelligent classification and summarization emphasizing key themes and trends
- Automated scheduled execution to ensure continuous content updates
- Fully automated closed-loop integration of web scraping, natural language processing, and instant messaging push
Core Problems Addressed
Traditional news summaries lack the capability to provide a longitudinal view of developments over multiple years. This workflow solves challenges related to cross-year data aggregation, information overload, and manual filtering. It enables efficient organization and insight extraction from historical tech news, helping users quickly grasp technological evolution and hotspot shifts.
Use Cases
- Technology media and news platforms producing regular historical review features
- Tech communities and industry observers compiling multi-year same-day major event summaries
- Researchers analyzing technology development trends and news dissemination patterns
- Individuals or teams automatically obtaining curated tech news digests to support decision-making and content creation
Main Process Steps
- Scheduled Trigger: Workflow initiates at a fixed time daily
- Generate Date List: Creates a list of historical dates to scrape, counting back from the current date to 2007
- Split and Process Dates Individually: Divides the date list and requests the Hacker News front page for each date sequentially
- Web Content Parsing: Extracts the headline titles and corresponding links for each day
- Data Merging and Structuring: Combines multi-date data into a unified JSON format
- Invoke Google Gemini Language Model: Performs classification, summarization, and trend analysis on the collected headlines, generating a Markdown summary
- Telegram Push: Sends the curated news summary to a designated Telegram channel for automatic publication
Involved Systems and Services
- Hacker News (data source)
- Google Gemini (PaLM) large language model (natural language understanding and generation)
- n8n automation platform (workflow orchestration)
- Telegram (content delivery)
Target Users and Value
- News editors and content planners: Automatically generate high-quality historical news feature content
- Technology researchers and analysts: Quickly access cross-year headline information to support trend analysis
- Community operators and information service providers: Efficiently maintain news push channels and enhance user engagement
- Professionals and enthusiasts interested in technology dynamics and industry evolution
This workflow deeply integrates automated historical news data collection, intelligent analysis, and multi-channel distribution, significantly improving information processing efficiency and content value. It serves as an excellent example of automated operation in technology news dissemination.