Sentiment Analysis of r/HongKong Using AFINN Lexicon

Sentiment Analysis for the Sub-Reddit “HongKong”

This post will perform sentiment analysis using AFINN. AFINN is a list of words rated for valence rated with an integer between minus five(negative) and plus five (positive). This implementation uses AFINN-en-165. ¹

This approach however is very naive as it does not build any models to determine the context of the usage of the word itself.

Interactive AFINN Sentiment Analysis

Below is a real-time sentiment analysis of Reddit’s r/HongKong subreddit using the AFINN lexicon. This React component demonstrates how AFINN categorizes comments as positive, negative, or neutral:

Note: Due to CORS restrictions, the live Reddit data may not load in modern browsers. The charts above show sample data to demonstrate the sentiment analysis functionality.

How AFINN Works

AFINN (Finn Årup Nielsen’s Dictionary) is a lexicon-based approach to sentiment analysis that:

1. Assigns scores to words (-5 to +5 scale)
2. Sums scores for all words in a text
3. Categorizes based on total score:
   • Positive score → Positive sentiment
   • Negative score → Negative sentiment
   • Zero score → Neutral sentiment

Benefits of Using MDX

This post demonstrates the power of MDX (Markdown + JSX) for blog posts:

1. Direct Component Import: React components can be imported and used directly in the content
2. Interactive Content: Rich, interactive demos embedded seamlessly in text
3. Better Developer Experience: TypeScript support, better tooling, and cleaner code
4. Performance: Astro islands ensure only necessary JavaScript is loaded
5. Flexibility: Mix static content with dynamic components as needed

References

1. AFINN Sentiment Analysis