tweets

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

1 row where display_text_range = "[12, 296]"

✎ View and edit SQL

This data as json, CSV (advanced)

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
1420188922504642563 swyx 33521530 2021-07-28T01:06:39+00:00 @AdamSinger look at it this way - I browse the available content at 2-3x, then slow down to absorb at 1x. If it is clearly valuable, I will replay multiple times + transcribe to progressively summarize (h/t @fortelabs) You do the same with articles & newsletters too! Scan, then read deeply.       Twitter Web App 1f89d6a41b1505a3071169f8d0d028ba9ad6f952 0 [12, 296] 1420183712717844482 14031032 AdamSinger       0 0 0 0 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]);