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The computer-science.SE did it, and I suggested it on cryptography.SE (and helped with a few entries)

I've no DSP background, but participating on SE taught me one thing: the longer a site existed, the more likely new questions are dups. So maybe it sends people onto the right track faster?

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    $\begingroup$ Welcome to SE.SP! That's a great idea! Can you please edit your question and give some links to examples on other SE sites, so we can see what you mean? $\endgroup$
    – Peter K. Mod
    Nov 24, 2023 at 16:32
  • $\begingroup$ Edited. Sorry, it's not Physics.SE, it's Computer Science SE, I remebered wrong. $\endgroup$
    – DannyNiu
    Nov 25, 2023 at 2:12
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    $\begingroup$ OK! I've started up a question copying (mostly) the CS.SE starter question. $\endgroup$
    – Peter K. Mod
    Nov 27, 2023 at 21:44

1 Answer 1

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To try to figure out what the top-level keywords are, I've exported all the tags from the site and generated a wordcloud that scales the tag label with the number of questions about that topic.

Code is:

from stackapi import StackAPI
SITE = StackAPI('dsp')
SITE.max_pages = 100
tags = SITE.fetch('tags')
word_frequency = {}
for i in tags['items']:
    word_frequency[i['name']] = i['count']

from wordcloud import WordCloud

wordcloud = WordCloud(width = 800, height = 800,
                background_color ='black',
                min_font_size = 10).fit_words(word_frequency)

wordcloud.to_file('word_cloud.png')

A word cloud generated by the tag frequency in SE.SP.

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