tweets

This is data scraped from swyx's timeline! See blog post

7 rows where in_reply_to_screen_name = "jakobgreenfeld" and user = 33521530 sorted by lang

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is_quote_status 2 ✖

user 1 ✖

  • swyx · 7 ✖

in_reply_to_screen_name 1 ✖

  • jakobgreenfeld · 7 ✖

created_at (date) 1 ✖

id user created_at full_text retweeted_status quoted_status place source truncated display_text_range in_reply_to_status_id in_reply_to_user_id in_reply_to_screen_name geo coordinates contributors is_quote_status retweet_count favorite_count favorited retweeted possibly_sensitive lang ▼ scopes
1468154498761650177 swyx 33521530 2021-12-07T09:44:44+00:00 @jakobgreenfeld got a chart for this but for product hunt?       Twitter for iPhone 95f3aaaddaa45937ac94765e0ddb68ba2be92d20 0 [16, 58] 1468143869426606081 1285142519525892098 jakobgreenfeld       0 0 1 0 0   en  
1468158323992059904 swyx 33521530 2021-12-07T09:59:56+00:00 @jakobgreenfeld that's some pretty damn quick number crunching skills there! i have another fun metric for you to try: Number of PH #1 of the day winners that now 404. it was roughly 10-15% when i checked 2017's winners in 2018 https://twitter.com/swyx/status/970106789189636098?s=20   970106789189636098 970106789189636098   Twitter Web App 1f89d6a41b1505a3071169f8d0d028ba9ad6f952 0 [16, 253] 1468157620741722121 1285142519525892098 jakobgreenfeld       1 0 4 0 0 0 en  
1468161588540547074 swyx 33521530 2021-12-07T10:12:54+00:00 @jakobgreenfeld dude today i was writing a DSL interpreter and it predicted this shit. wasnt accurate but was pretty close. meaning it understands AST traversal/language interpreter type stuff 🤯 https://twitter.com/swyx/status/1468161588540547074/photo/1       Twitter Web App 1f89d6a41b1505a3071169f8d0d028ba9ad6f952 0 [16, 195] 1468159751305449475 1285142519525892098 jakobgreenfeld       0 0 2 0 0 0 en  
1468168056983592963 swyx 33521530 2021-12-07T10:38:36+00:00 @jakobgreenfeld the fact that ~2% of 2021's winners are already dead...       Twitter Web App 1f89d6a41b1505a3071169f8d0d028ba9ad6f952 0 [16, 71] 1468165838318538758 1285142519525892098 jakobgreenfeld       0 0 2 0 0   en  
1468168672602583040 swyx 33521530 2021-12-07T10:41:03+00:00 @jakobgreenfeld or the charitable explanation is that 7-8% bitrot is "normal" baseline, and vintages 2015-2018 have more age and therefore more bitrot or maybe around 2018 people started realizing that even if the project is dead they should at least 302 it to the next thing       Twitter Web App 1f89d6a41b1505a3071169f8d0d028ba9ad6f952 0 [16, 276] 1468167107569455107 1285142519525892098 jakobgreenfeld       0 0 3 0 0   en  
1468156519808131075 swyx 33521530 2021-12-07T09:52:46+00:00 @jakobgreenfeld ☠️       Twitter for iPhone 95f3aaaddaa45937ac94765e0ddb68ba2be92d20 0 [16, 18] 1468155042813419520 1285142519525892098 jakobgreenfeld       0 0 1 0 0   und  
1468159004132052992 swyx 33521530 2021-12-07T10:02:38+00:00 @jakobgreenfeld https://twitter.com/swyx/status/1468159004132052992/photo/1       Twitter Web App 1f89d6a41b1505a3071169f8d0d028ba9ad6f952 0 [15, 15] 1468154599290949638 1285142519525892098 jakobgreenfeld       0 0 2 0 0 0 und  

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CREATE TABLE [tweets] (
   [id] INTEGER PRIMARY KEY,
   [user] INTEGER REFERENCES [users]([id]),
   [created_at] TEXT,
   [full_text] TEXT,
   [retweeted_status] INTEGER,
   [quoted_status] INTEGER,
   [place] TEXT REFERENCES [places]([id]),
   [source] TEXT REFERENCES [sources]([id]), [truncated] INTEGER, [display_text_range] TEXT, [in_reply_to_status_id] INTEGER, [in_reply_to_user_id] INTEGER, [in_reply_to_screen_name] TEXT, [geo] TEXT, [coordinates] TEXT, [contributors] TEXT, [is_quote_status] INTEGER, [retweet_count] INTEGER, [favorite_count] INTEGER, [favorited] INTEGER, [retweeted] INTEGER, [possibly_sensitive] INTEGER, [lang] TEXT, [scopes] TEXT,
   FOREIGN KEY([retweeted_status]) REFERENCES [tweets]([id]),
   FOREIGN KEY([quoted_status]) REFERENCES [tweets]([id])
);
CREATE INDEX [idx_tweets_source]
    ON [tweets] ([source]);