Developer Builds Real-Time Sentiment Analyzer for Hacker News and Reddit Using VADER

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A developer has created an open-source sentiment analysis tool that fetches posts from Hacker News and Reddit and scores them using VADER, a rule-based natural language processing model optimized for social media text. The tool classifies each post as positive, neutral, or negative based on a compound score ranging from -1 to +1, and also extracts keywords and engagement metrics. VADER was chosen over large language models for its speed, processing over 10,000 posts per second, its zero cost, and its consistent, reproducible results. The analyzer is deployable via Apify and supports configurable inputs such as subreddit selection, post volume, and sentiment filtering. It is also available through a RapidAPI endpoint and a public GitHub repository as part of a broader content extraction tool suite.

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ProgrammingDEV Community ·

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