Using the HN public dataset in Google BigQuery [0], which I think fits easily in the amount of free queries allowed:
SELECT
EXTRACT(YEAR FROM timestamp) AS year,
SUM(CASE WHEN text LIKE '%—%' THEN 1 ELSE 0 END) AS withDash,
COUNT(*) AS total,
SUM(CASE WHEN text LIKE '%—%' THEN 1 ELSE 0 END) / COUNT(*) AS fraction
FROM `bigquery-public-data.hacker_news.full`
WHERE type = 'comment'
GROUP BY year
ORDER BY year;
year with— total frac
2006 0 12 0.000
2007 13 70858 0.000
2008 461 247922 0.001
2009 1497 491034 0.003
2010 3835 842438 0.005
2011 4719 1044913 0.005
2012 5648 1246782 0.005
2013 7881 1665185 0.005
2014 8400 1510814 0.006
2015 9967 1642912 0.006
2016 12081 2093612 0.006
2017 14530 2361709 0.006
2018 19246 2384086 0.008
2019 23662 2755063 0.009
2020 27316 3243173 0.008
2021 32863 3765921 0.009
2022 34657 4062159 0.009
2023 36611 4221940 0.009
2024 32543 3339861 0.010
2025 30608 2231919 0.014
Querying for the users who use "—" most as a proportion of all their comments:
SELECT
`by`,
SUM(CASE WHEN text LIKE '%—%' THEN 1 ELSE 0 END) / COUNT(*) AS fraction,
COUNT(*) AS total,
MIN(timestamp) AS minTime,
MAX(timestamp) AS maxTime
FROM `bigquery-public-data.hacker_news.full`
WHERE
type = 'comment' AND
timestamp < '2022-11-30'
GROUP BY `by`
HAVING COUNT(*) > 100
ORDER BY fraction DESC
LIMIT 250;
[0] https://console.cloud.google.com/marketplace/product/y-combi...
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