Google BigQueryのHN公開データセットを使って、無料で許可されているクエリの範囲内で簡単にできると思うよ: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 だから、確実に増えてるね。「—」を使うユーザーの割合を全コメントに対して調べるクエリ: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 100 ORDER BY fraction DESC LIMIT 250; zmgsabstが最も多く使ってる [1]、westoncb [2]は4番目に多い古いアカウントだよ。