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content/blog/survey-02/index.md

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@@ -14,10 +14,10 @@ We will now go through the results in the same order as the questions were asked
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![Excitement barplot](excitement.png)
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On average, readers are excited about the newsletter (p-value for t-test of mean 3 is 9.9e-5). The mean excitement level is 3.6 out of 5, the median is 4.
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On average, readers are excited about the newsletter (the p-value for a t-test of mean 3 is 9.9e-5). The mean excitement level is 3.6 out of 5, the median is 4.
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Our 95% confidence interval is [3.32, 3.91] using a standard error of 0.15.
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These are fairly nice results. Annecdotally, we got a lot of messages about issues with the newsletter and how to improve it,
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These are fairly nice results. Anecdotally, we got a lot of messages about issues with the newsletter and how to improve it,
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so we are happy to see that the excitement is still high. Still, the data shows that we have room for improvement.
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## Content Quantity
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![Newsletter frequency barplot](frequency.png)
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73% of readers are either happy with the current frequency or don't care. A minority of 21% would like the newsletter become quarterly.
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Arguments we've heard for this are that a lower frequency would allow editors improve the quality that goes into each newsletter.
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73% of readers are either happy with the current frequency or don't care. A minority of 21% would like the newsletter to become quarterly.
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Arguments we've heard for this are that a lower frequency would allow editors to improve the quality that goes into each newsletter.
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Counterarguments include that a lower frequency would make the newsletter less timely.
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Things like calls for playtesters or job offers would be less useful if they are only sent out every three months.
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Things like calls for playtesters or job offers would be less useful if they were only sent out every three months.
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## AI
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If we interpret the answers as a scale of 1-5, where 1 is "not okay at all" and 5 is "I love it", the mean answer was 2.25, the median 2.
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Notably, the mode is tied at 1 and 2. The 95% confidence interval is [1.89, 2.61] using a standard error of 0.18.
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People are generally against using an LLM to generate summaries
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(p-value of t-test of mean 3 is 1.2e-4).
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(the p-value of a t-test of mean 3 is 1.2e-4).
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While a majority of readers (65%) are at least okay with AI-generated summaries, a significant minority (35%) are not okay at all with this proposal.
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These include very active members of the community and
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contributors who have announced that they would no longer want their content to be included in the newsletter if AI was used.
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Of note is that the verbal feedback we got indicated that a lot of readers did not fully understand what exactly was being proposed.
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People worried that we would start generating a majority of the newsletter or entire sections with AI, which is definitely not something any of us wants.
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People worried that we would start generating a majority of the newsletter or entire sections with AI, which is not something any of us wants.
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Some readers also thought we already started using LLMs.
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The actual idea was to use AI to generate summaries of articles that were already hand-picked by the editors but not summarized yet because of time constraints.
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The summaries would then be edited and verified by the editors. The extent to which AI would be used would be limited to up to two sentences per late article.
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Any confusion in this regard is our fault.
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We will try to be more clear on such questions in the future.
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Although this misunderstanding might have skewed the results, we have reason to believe that the effect is not too large.
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Annecdotally, when we properly explained the proposal to readers who were against it,
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Anecdotally, when we properly explained the proposal to readers who were against it,
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most did not change their mind and cited deontological reasons for their stance.
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Chief among these was solidarity with the large amount of creatives who recently lost their jobs due to AI-generated content,
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Chief among these was solidarity with the large number of creatives who recently lost their jobs due to AI-generated content,
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inside and outside the game development industry.
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## Tone
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The majority of readers (61.5%) have not yet contributed to the newsletter and 26.9% contributed 2-5 times.
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Only 3.8% contributed exactly once, while the rest (7.7%) are heavy contributors, helping us out more than five times.
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While it might seem weird that more people contriubted 2-5 times than exactly once,
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While it might seem weird that more people contributed 2-5 times than exactly once,
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keep in mind that the former is the sum of people who contributed twice, thrice, four times, and five times.
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The reason we binned these together is that we are interested in the following categories:
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- Pure readers
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![Ease barplot](ease.png)
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The mean ease of contributing is 3.0, the median 3. The 95% confidence interval is [2.5, 3.6] using a standard error of 0.26.
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The mean ease of contributing is 3.0, and the median is 3. The 95% confidence interval is [2.5, 3.6] using a standard error of 0.26.
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Readers generally feel neutral about the ease of contributing to the newsletter (p-value of t-test of mean 3 is 0.87).
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Readers generally feel neutral about the ease of contributing to the newsletter (the p-value of a t-test of mean 3 is 0.87).
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It's clear we can do better here, but we are not sure yet how.
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We can do better here, but we are not sure yet how.
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We'd love to hear your ideas on [GitHub](https://github.com/rust-gamedev/rust-gamedev.github.io/issues/1519) or on Discord (ping @janhohenheim).
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## Keeping up with the newsletter
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We can see the shift from X / Twitter to Mastodon reported by many OSS communities in our readers as well.
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The fediverse is not looking as popular as an alternative to Reddit yet, with no reader reporting it as a source of information.
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The "Email" option in the survey is meant for people who have setup some kind of email alerts manually.
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The "Email" option in the survey is meant for people who have set up some kind of email alerts manually.
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Per written feedback, a lot of people want to see propper email subscription implemented. While this was a goal for this month,
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we did not manage to implement it yet because of personal things that came up for Jan Hohenheim, who volunteered to implement it.
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Per written feedback, a lot of people want to see proper email subscriptions implemented. While this was a goal for this month,
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we have not managed to implement it yet because of personal things that came up for Jan Hohenheim, who volunteered to implement it.
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We will try to get this done for the next newsletter.
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## What is going well
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![What is going well wordcloud](like.png)
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This was a free-text question. The above is a wordcloud of the answers with some obvious words like "game" or "newsletter" removed.
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Note that the inclusion of the word "ai" is misleading, as it was only mentioned in texts like "I like that we don't use AI, please do".
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This was a free-text question. The above is a word cloud of the answers with some obvious words like "game" or "newsletter" removed.
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Note that the inclusion of the word "AI" is misleading, as it was only mentioned in texts like "I like that we don't use AI, please do".
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Going through the feedback by hand, common things readers enjoy about the newsletter are:
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- A good mix of content
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![Comments wordcloud](comment.png)
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This last free-text question was meant for any additional comments readers might have.
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The wordcloud above is dominated by one sentence: "Thank you for your work". Thank you very very much for your kind words!
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The word cloud above is dominated by one sentence: "Thank you for your work". Thank you very very much for your kind words!
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We are working on this newsletter in our free time because we love the community and Rust game development, so reading this means a lot to us.
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## Correlations
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We were interested in how the responses of some questions correlated with how much people had already contributed to the newsletter.
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We were interested in how the responses to some questions correlated with how much people had already contributed to the newsletter.
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Long story short: it seems like there is no significant correlation between how much people contributed and how they answered the other questions.
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Let's look at the correlations in turn now.
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![Excitement correlation](excitement_contributions.png)
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Our hypothesis was that people who contributed more to the newsletter would be more excited about it.
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We found no evidence for this (p-value of Jonckheere-Terpstra test for increasing trend is 0.986).
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Based on the plot above, we then hypothesized that the opposite might be true, namely that frequent contributers are less excited for the newsletter.
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We hypothesized that people who contributed more to the newsletter would be more excited about it.
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We found no evidence for this (the p-value of a Jonckheere-Terpstra test for increasing trend is 0.986).
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Based on the plot above, we then hypothesized that the opposite might be true, namely that frequent contributors are less excited about the newsletter.
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This actually might be the case (p-value is 0.021), but do not take this as a strong result.
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It is a post-hoc hypothesis and the resulting p-value is not very low considering the number of tests we run in this analysis.
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It is a posthoc hypothesis and the resulting p-value is not very low considering the number of tests we run in this analysis.
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For these reasons, we do not consider this result to be significant.
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### Feelings About AI By Contributions
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![AI correlation](ai_contributions.png)
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We hypothesized that there would be a correlation between how much people contributed to the newsletter and how they felt about AI-generated summaries.
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We found no evidence for this (p-value of Jonckheere-Terpstra test for a two-sided alternative is 0.57).
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We found no evidence for this (the p-value of a Jonckheere-Terpstra test for a two-sided alternative is 0.57).
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### Ease of Contributing By Contributions
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![Ease correlation](ease_contributions.png)
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We hypothesized that there would be a correlation between how much people contributed to the newsletter and how easy they found it to contribute.
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We hypothesized that there would be a correlation between how much people contributed to the newsletter and how easily they found it to contribute.
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We found no evidence for this (p-value of Jonckheere-Terpstra test for a two-sided alternative is 0.25).
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We found no evidence for this (the p-value of a Jonckheere-Terpstra test for a two-sided alternative is 0.25).
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## Conclusion
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