1,151 karma · joined February 2, 2015
On paying for this. When data operations are built around pipelines, it's often easier to re-run the pipeline or restore a snapshot. Which requires a good server, but not a service. So before paying, I'd check why the new tool is better.
An example: https://github.com/antontarasenko/smq/blob/master/reports/ha...
Its discussion: https://news.ycombinator.com/item?id=11499120
An explanation: https://news.ycombinator.com/item?id=11499158
So, what's happened to them? It's interesting to hear your Show HN project's story.
And, yes, supporting links:
Top 100 "Show HN" Projects in 2006–2015: https://github.com/antontarasenko/smq/blob/master/reports/ha...
Top 100 "Show HN" Projects plotted: https://plot.ly/~AntonTarasenko/20/top-100-show-hn-submissio...
Top 5,000 "Show HN" Projects plotted (this submission's link): https://plot.ly/~AntonTarasenko/23/top-5000-show-hn-submissi...
Top 10,000 "Show HN" Projects CSV: https://drive.google.com/open?id=0B-fi5DaWfQWbdlVKMU84czFrNk...
The data from: https://github.com/antontarasenko/smq
After SeanDav's question and minimaxir's comment, I summed up reposts' scores before computing the mean and the median:
HN news sources by mean score: https://docs.google.com/spreadsheets/d/1tTDDG2xg7OVKdUy4WCZ_...
HN news sources by median score: https://docs.google.com/spreadsheets/d/1P20sKg-fI6msZVZtJFe0...
HN news sources by number of submissions: https://docs.google.com/spreadsheets/d/1mmfbNWaX0Nr1P65VmwZp...
SQL code: https://github.com/antontarasenko/smq/blob/master/hackernews...
1. Sorting by the median. The mean is not very informative for the quality of the source. Most sources provide low-scored content with eventual hits that drive the mean up. The median fixes this problem.
2. Cutting off at 10 submissions. An arbitrary minimum to exclude pure luck from the results.
In the end, this ranking excludes websites like github.com and youtube.com, but it features some less known sources.
Also, ranking by category: https://github.com/antontarasenko/smq/blob/master/reports/ha...
Previous discussions about HN's dataset on BigQuery:
* https://news.ycombinator.com/item?id=10440502 * https://news.ycombinator.com/item?id=10979365
Apart from these queries, what do you want to know about NH content?
It's okay if a company doesn't need capital, but even tech firms take $50-100M a year to grow.
Again, if your sector consists of nonprofits, you may do fine. But IT and finance are for profit industries, with rare exceptions.
If only non-profits work with your problem, then ask them what tech solutions they need. In some cases, they don't need technology at all, but rather funding or government support.
I would avoid "feeling good" non-profits that spend grands on noble but futile activities. Most useful solutions are those that people buy, instead of getting for free.
I'd be glad to point at non-profits in the area you're interested in.
Many expensive ideas are embodied in patents and code.
Cheap ideas exist, but not all ideas are cheap.
PS: A very nice tool!
Agreed on making something great as the end. But delivering the product to the audience is important for niche products. Then factors like time, website, text become important (when they matter).
"How are stories ranked?
On the front page, by points divided by a power of the time since they were submitted. Comments in comment threads are ranked the same way.
Stories on the new page and comments on the comments page are listed chronologically."
Now, try to find a similar answer for the websites like Facebook or Quora.
As for the metrics, being on the front page seems to drive less motivated traffic. When a user upvotes the link, he cares. When the link gets to the front page, users click it because it's on the top, not because they're interested.
Hence, sales or whatever, but one should be interested in upvotes as the indicator, not the front page.
And computers still do a lousy job in talking to people. Try to make people to answer a 10-question online survey. Harder to motivate than in face-to-face meetings.
I mean, the whole argument about "bigger money" at startups is more like a myth.
Rather, we should talk about "more research is needed to get a representative sample of studies of a phenomena."
Also see Figure 1 for the evidence of prices highly varying over time. It implies that different users pay different prices within small periods of time.