Key takeaways:
- OpenAI has a developer community forum with over 100,000 posts and 20,000 users.
- The dataset of posts from common categories provides insights into developer sentiment and shared experiences with OpenAI products.
- Vector embeddings, sentiment analysis, and topic models were computed to better understand the dataset.
- Negative sentiment is more prevalent in API and API/bugs categories, while positive sentiment is more common in community and gpts-builders/plugin-store categories.
GENERATED SUMMARY
OpenAI's developer community forum, hosted by Discourse, is a valuable resource for understanding developer sentiment and shared experiences with OpenAI products. Launched in March 2021, the forum has seen over 100,000 posts from over 20,000 users, making it a rich source of data for analyzing developer experiences.
The dataset includes posts from common categories such as API, GPT Builders, Prompting, Community, and Documentation. By focusing on these categories, the dataset provides a more targeted view of developer interactions with OpenAI products.
To extract deeper insights, sentiment analysis, vector embeddings, and topic models were computed for the dataset. The sentiment analysis revealed that, on average, most posts are neutral. However, the distribution of sentiment varies by category, with the API and API/bugs categories having the most negative sentiment. On the other hand, the community and gpts-builders/plugin-store categories have the most positive sentiment.
Vector embeddings were computed using Nomic Embed-Text v1.5, which allows for future applications due to its Matryoshka resizable nature. The cumulative distributed frequency graph showed that 99.7% of posts have a length less than 8192 characters, indicating that post_content_raw can be vectorized without worrying about significant knowledge or data loss.
Topic models were also computed, with the medium topic model having 256 topics and the broad topic model having 8 topics. These models can help identify common themes and trends in the dataset.
In summary, OpenAI's developer community forum is a valuable resource for understanding developer sentiment and shared experiences with OpenAI products. The dataset, which includes posts from common categories, provides insights into developer interactions with OpenAI products. Sentiment analysis, vector embeddings, and topic models were computed to better understand the dataset, revealing that negative sentiment is more prevalent in API and API/bugs categories, while positive sentiment is more common in community and gpts-builders/plugin-store categories.