65% of Hacker News Posts Have Negative Sentiment, and They Outperform (philippdubach.com)

A new empirical study analyzing the sentiment of posts on Hacker News reveals that 65% of content carries a negative sentiment, yet these posts outperform their more positive counterparts, averaging 35.6 points compared to the overall average of 28 points—a striking 27% performance premium. This research encompasses an extensive dataset of 32,000 posts and 340,000 comments, employing a variety of sentiment analysis models, including transformer-based classifiers like DistilBERT and RoBERTa as well as large language models such as Llama and Mistral. The findings suggest that negativity, specifically critical commentary about technology and industry practices, could be a significant driver of engagement, raising questions about the relationship between sentiment and content visibility. The implications of this study are noteworthy for the AI and machine learning community as it highlights the performance dynamics of sentiment analysis in predicting user engagement. It also emphasizes the need for accurate calibration of sentiment classifiers, especially since the trend of negativity persisted across multiple models. As the researcher prepares to share the code, dataset, and a dashboard for tracking Hacker News posts, these insights could pave the way for further exploration into content engagement metrics and sentiment's role in shaping discussion on tech platforms.