Contains cast data since November, 1st 2024, enriched with categories, topics, embeddings, ML features and language.
Updated every 2 hours, lagging 2 to 3 hours behind real time data.
| Column | Type | Description |
|---|---|---|
| day | DATE | YYYY-MM-DD |
| timestamp | TIMESTAMP | Cast timestamp as recorded by the Farcaster hub. |
| hash | STRING | Cast hash. |
| fid | INTEGER | Author fid. |
| user_name | STRING | Author username at time of cast. |
| num_follower | INTEGER | Author's number of followers at time of cast. |
| num_follower_bin | INTEGER | num_follower bin from 0 to 9, based on the same hour distribution. |
| num_following | INTEGER | Author's number of followed accounts at time of cast. |
| num_following_bin | INTEGER | num_following bin from 0 to 9, based on the same hour distribution. |
| num_casts_same_hour | INTEGER | Number of times the user casted in the same hour. |
| text | STRING | Cast text. |
| text_len | INTEGER | Cast text length. |
| text_len_bin | INTEGER | text_len bin from 0 to 9, based on the same hour distribution. |
| embeds | JSON | Array of embeddings as recorded by the Farcaster hub. |
| mentions | JSON | Array of mentions. As recorded by the Farcaster hub. |
| mentions_pos | JSON | Array of mentions positions. As recorded by the Farcaster hub. |
| embeds_num | INTEGER | Number of embeddings. |
| mentions_num | INTEGER | Number of mentions. |
| parent_fid | INTEGER | Parent cast fid when it's a reply. |
| parent_hash | STRING | Parent cast hash when it's a reply. |
| parent_url | STRING | Parent url when it's casted in a channel. |
| category | INTEGER | Category classification into one of 11 categories. |
| category_label | STRING | Category label, one of c_arts, c_business, c_crypto, c_culture, c_misc, c_money, c_nature, c_politics, c_sports, c_tech_science. |
| topic | INTEGER | Topic classification into one of 60 topics. |
| topic_label | STRING | Topic label. |
| q_clear | INTEGER | Is it clear? (from 0 to 100) |
| q_audience | INTEGER | Does it have a clear target audience? (from 0 to 100) |
| q_info | INTEGER | Is it informative? (from 0 to 100) |
| q_easy | INTEGER | Is it easy to understand for the general layman public? (from 0 to 100) |
| q_verifiable | INTEGER | Is it verifiable online? (from 0 to 100) |
| q_personal | INTEGER | Is it personal? (from 0 to 100) |
| q_funny | INTEGER | Is it funny? (from 0 to 100) |
| q_meme_ref | INTEGER | Is it a reference to a well known meme? (from 0 to 100) |
| q_emo_res | INTEGER | Does it elicit an emotional response? (from 0 to 100) |
| q_happiness | INTEGER | Does it convey happiness? (from 0 to 100) |
| q_curiosity | INTEGER | Does it trigger curiosity? (from 0 to 100) |
| q_aggressivity | INTEGER | Is it aggressive? (from 0 to 100) |
| q_surprise | INTEGER | Does it have an element of surprise? (from 0 to 100) |
| q_interesting_ask | INTEGER | Does it ask an interesting question? (from 0 to 100) |
| q_call_action | INTEGER | Does it come with an explicit call to action? (from 0 to 100) |
| c_xxx | INTEGER | c_columns indicate how likely the cast is to be in that category. (from 0 to 100) |
| t_xxx | INTEGER | t_columns indicate how likely the cast is to be in that topic. (from 0 to 100) |
| dim_1 to dim_32 | FLOAT | Reduced embedding dimensions. These were calculated such that, when combined with the q_, c_ and t_ features, will conserve 50% variance from the original 512 dimensions embedding. |
| predict_like | INTEGER | Output of the Likemeter model (0 to 100). |
| language | STRING | Autodetected language from the text. |