tweets

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

1 row where quoted_status = 1433807042590875654 and retweeted = 0 sorted by lang

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user 1 ✖

retweeted 1 ✖

retweet_count 1 ✖

  • 1 1

quoted_status 1 ✖

  • 1433807042590875654 · 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
1433918146348343297 swyx 33521530 2021-09-03T22:21:41+00:00 I think why I struggle with OKRs so much: Suits set them as a system of external control, a way to manage by spreadsheet rather than get hands dirty, defining quality as quantity, when the best work of knowledge workers and creatives comes from doing epic shit for the sake of it. https://twitter.com/petergyang/status/1433807042590875654   1433807042590875654 1433807042590875654   Twitter for iPhone 95f3aaaddaa45937ac94765e0ddb68ba2be92d20 0 [0, 280]             1 1 30 0 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]);