tweets

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

1 row where in_reply_to_user_id = 84490044 sorted by lang

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source 1 ✖

in_reply_to_user_id 1 ✖

  • 84490044 · 1 ✖

favorited 1 ✖

  • 0 1

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
1433807042590875654 Peter Yang 84490044 2021-09-03T15:00:12+00:00 You look more into this space and realize it's the opposite of your job. There are no OKRs, no metrics, no career ladders, not even that many PMs. People are just building stuff because they're passionate about it.       Typefully 295366d0fb34352a1961af2413827f072adefdb9 0 [0, 216] 1433807041403916296 84490044 petergyang       0 27 431 0 0   en  

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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]);