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Hi lately I was focused on theoretical modeling of heavy-tailed data. However, I find it hard to collect some classic heavy-tailed data for experiments. I wonder if there is any public and well-known (better if any) dataset confirmed to be heavy-tailed from Kaggle or some labs ?

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The types of heavy-tailed distributions (wikipedia) gives an overview, and I'd start with Pareto or Log-normal. The hard part will be finding just one dataset!

I'd start with Log-normal, and then going to this page, you see sources for this distribution:

enter image description here

Let's pick one of the easier ones to find: Length of Spoken Words. (Note that written words is not lognormal - source.)

And to keep it relevant, there is good structured data for US Presidential (Campaign) speeches. You mentioned Kaggle, so here is one example:

https://www.kaggle.com/alandu20/2016-us-presidential-campaign-texts-and-polls

Collection of data from the 2016 U.S. Presidential Election Campaign containing:

1 Transcripts of the three presidential debates, divided into separate Trump and Clinton text files

2 Transcripts of Trump's 64 speeches delivered after the RNC and Clinton's 35 speeches delivered after the DNC

3 Transcripts of select speeches delivered by candidates during the primary campaigns

4 USC Dornsife/LA Times Presidential Election Poll, with daily breakdown by voter groups

5 Five Thirty Eight Election Poll, containing daily data from numerous pollsters

1, 2 or 3 would work.


For the record, there are MANY ways of collecting heavy-tailed data, and this is just an example of one way to get started...


for fun, quick analysis from 2016 election:

enter image description here

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