tweets

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

1 row where favorited = 0, retweeted = 1 and user = 115513801 sorted by lang

✎ View and edit SQL

This data as json, CSV (advanced)

user 1 ✖

retweeted 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
1421095739195756549 Tj 115513801 2021-07-30T13:10:01+00:00 This talk on Growing a Meta-Language by @swyx is just amazing! He goes in depth into talking about the how the trifecta of language+flavour+tools help each other. https://www.youtube.com/watch?v=18F5v1diO_A Playing around with @rails, I see the same kind of magic that makes it charming to use!       Twitter Web App 1f89d6a41b1505a3071169f8d0d028ba9ad6f952 0 [0, 276]             0 2 9 0 1 0 en  

Advanced export

JSON shape: default, array, newline-delimited, object

CSV options: 

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]);