Updated readme with AI generated summary of statistics.
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README.md
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# dRStats
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# dR stats
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Project to determine health of the devrant platform.
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This project is made to determine the health of the devRant developer community.
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Also this data will be used for retoor9b, the newest AI hype! You're still using ChatGPT?
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Also this data will be used for retoor9b, the newest AI hype! You're still using ChatGPT?
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@ -10,7 +10,7 @@ Click here for latest [dataset](https://retoor.molodetz.nl/retoor/drstats/src/br
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Click here for latest [graphs compilaiton](https://retoor.molodetz.nl/retoor/drstats/src/branch/main/export/1_graphs_compliation.png).
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Click here for latest [graphs compilaiton](https://retoor.molodetz.nl/retoor/drstats/src/branch/main/export/1_graphs_compliation.png).
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Click here for all generated [data](https://retoor.molodetz.nl/retoor/drstats/src/branch/main/export)
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Click here for all generated [data](https://retoor.molodetz.nl/retoor/drstats/src/branch/main/export). It's a big dataset containing data for LLM's to train on, graphs per user or overal statistics and json files with all made observations.
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Statistics are build automatically using a build server.
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Statistics are build automatically using a build server.
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@ -42,3 +42,37 @@ If you type `dr.` in terminal and press tab you'll see all available apps auto c
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4. `dr.rant_stats_per_day` exports graphs to export folder. don't forget to execute `dr.sync` first.
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4. `dr.rant_stats_per_day` exports graphs to export folder. don't forget to execute `dr.sync` first.
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5. `dr.rant_stats_per_hour` exports graphs to export folder. don't forget to execute `dr.sync` first.
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5. `dr.rant_stats_per_hour` exports graphs to export folder. don't forget to execute `dr.sync` first.
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6. `dr.rant_stats_per_weekday` exports graphs to export folder. don't forget to execute `dr.sync` first.
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6. `dr.rant_stats_per_weekday` exports graphs to export folder. don't forget to execute `dr.sync` first.
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## Observations made by AI regarding statistics
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The model used for generating these observations is called `smoll2` which is a 1.7b model.
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Provided report below does contain some inconvenience but I'm working on it by testing several models. I am limited by the power my server provides for running LLM's. I do not own a decent GPU.
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If I would attach the ChatGPT API to my project, the statistics would be better / perfect. I have tested this. Sadly, the API costs to much for a hobby project and I refuse the use of an credit card. There are better options for payment not provided by OpenAI which I prefer.
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### Several trends and insights about the devRant community
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1. The most active users seem to be posting more than once per month. This
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could indicate that these individuals are very engaged with the community
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or have a high level of interest in participating in discussions.
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2. There is a large range in the post lengths, ranging from 19 characters
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(kienkhongngu) to 742 characters (Pogromist). While there may be some
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outliers due to formatting issues or other factors, this suggests that
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users have varying levels of engagement and writing style on the forum.
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3. The "ownership_content" value ranges from -0.5 to 1. This indicates
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that while some users do not post much, others are heavily involved with
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frequent and in-depth contributions. However, it's unclear what specific
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metric this represents or how it correlates with user engagement.
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4. The most common "upvotes" per month range from 0 to 9 (arekxv) and 21
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(-1 for negative upvotes). This suggests that while users are posting
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relatively often, there may be some variability in their level of
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agreement with the content they're sharing or commenting on.
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5. Overall, the data indicates a moderate level of engagement from users.
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While there is no clear indication of highly active users dominating the
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forum, the overall statistics suggest an engaged community where users
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contribute regularly and interact with each other's posts.
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