We have some trend analysis in stack overflow. Like this one: http://hewgill.com/~greg/stackoverflow/stack_overflow/tagtrend.html.

And I can also see the overall count of questions based on each tag, as shown below:

enter image description here

However, understanding the trending of questions could also be interesting as we can have a better understanding on what people are learning and what the industry in focusing on. By comparing things like Visualforce and lightning we might have a better understanding of the market share as well.

Has anyone done some work on this?

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I did some simple search terms based on tag, date, and a few other filters. Some example terms:

[visualforce] is:question created:2016-09
[lightning] is:answer created:2015-01
isaccepted:yes created:2016-01

Just looking at the two tags you singled out and comparing them to the system totals, here's the data from last September (when the first [lightning] questions started appearing) through the end of last month:

Tag          Total Questions  Total Answers  Total Accepted  Answers/Question  Accept %
all          19936            21528          7968            1.08              39.97%
visualforce  3950             4331           1677            1.10              42.46%
lightning    498              435            174             0.87              34.94%

So [visualforce] questions are answered at a slightly higher frequency than questions in general, and are also slighlty more likely to have an accepted answer. In contrast, [lightning] questions see notably fewer answers, and are also less likely to have an accepted answer.

Here are some charts from the beginning of last year:




Accept %

As you can see, [lightning] is gaining some ground, but [visualforce] is actually holding fairly steady with a pretty flat trend line this year, and still more popular than at the start of 2015.

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  • Hi Adrian, how did you generate this graph? Did you use Data Explorer? I'm keen to how the [marketing-cloud] tag is trending. – Eliot Harper Oct 23 '16 at 22:46
  • Just dumped search results into a Google Sheet. @Eliot – Adrian Larson Oct 23 '16 at 23:03

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