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Xiaohongshu-AIGC-comments (including Posts)dataset

Xiaohongshu-AIGC-comments

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset

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About this Dataset

Xiaohongshu-AIGC-comments (including Posts)dataset

This dataset is collected from the Xiaohongshu (Little Red Book) platform, focusing on user-generated content about Artificial Intelligence-Generated Content (AIGC). It covers various categories, including advertisement, automotive, fashion, food, literature, printing, sports, and technology. The dataset contains user comments and posts, with information such as user IDs, content, timestamps, likes, and sentiment analysis, which can be used to analyze public perceptions and attitudes toward AIGC.

Tables

Comments Additional

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.comments_additional
  • 316.38 kB
  • 7,744 rows
  • 14 columns
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CREATE TABLE comments_additional (
  "comment_id" VARCHAR,
  "create_time" BIGINT,
  "ip_location" VARCHAR,
  "note_id" VARCHAR,
  "content" VARCHAR,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "sub_comment_count" DOUBLE,
  "pictures" VARCHAR,
  "parent_comment_id" VARCHAR,
  "last_modify_ts" DOUBLE,
  "like_count" DOUBLE,
  "sentiment" VARCHAR
);

Comments Advertising Planning

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.comments_advertising_planning
  • 621.15 kB
  • 7,514 rows
  • 14 columns
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CREATE TABLE comments_advertising_planning (
  "comment_id" VARCHAR,
  "create_time" BIGINT,
  "ip_location" VARCHAR,
  "note_id" VARCHAR,
  "content" VARCHAR,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "sub_comment_count" DOUBLE,
  "pictures" VARCHAR,
  "parent_comment_id" VARCHAR,
  "last_modify_ts" DOUBLE,
  "like_count" DOUBLE,
  "sentiment" VARCHAR
);

Comments Brand Marketing

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.comments_brand_marketing
  • 321.32 kB
  • 3,739 rows
  • 14 columns
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CREATE TABLE comments_brand_marketing (
  "comment_id" VARCHAR,
  "create_time" BIGINT,
  "ip_location" VARCHAR,
  "note_id" VARCHAR,
  "content" VARCHAR,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "sub_comment_count" BIGINT,
  "pictures" VARCHAR,
  "parent_comment_id" VARCHAR,
  "last_modify_ts" BIGINT,
  "like_count" BIGINT,
  "sentiment" VARCHAR
);

Comments Car

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.comments_car
  • 1.14 MB
  • 10,560 rows
  • 14 columns
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CREATE TABLE comments_car (
  "comment_id" VARCHAR,
  "create_time" BIGINT,
  "ip_location" VARCHAR,
  "note_id" VARCHAR,
  "content" VARCHAR,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "sub_comment_count" BIGINT,
  "pictures" VARCHAR,
  "parent_comment_id" VARCHAR,
  "last_modify_ts" BIGINT,
  "like_count" BIGINT,
  "sentiment" VARCHAR
);

Comments Drawing

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.comments_drawing
  • 452.91 kB
  • 9,246 rows
  • 14 columns
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CREATE TABLE comments_drawing (
  "comment_id" VARCHAR,
  "create_time" BIGINT,
  "ip_location" VARCHAR,
  "note_id" VARCHAR,
  "content" VARCHAR,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "sub_comment_count" BIGINT,
  "pictures" VARCHAR,
  "parent_comment_id" VARCHAR,
  "last_modify_ts" BIGINT,
  "like_count" VARCHAR,
  "sentiment" VARCHAR
);

Comments Fashion

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.comments_fashion
  • 948.08 kB
  • 9,453 rows
  • 14 columns
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CREATE TABLE comments_fashion (
  "comment_id" VARCHAR,
  "create_time" BIGINT,
  "ip_location" VARCHAR,
  "note_id" VARCHAR,
  "content" VARCHAR,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "sub_comment_count" BIGINT,
  "pictures" VARCHAR,
  "parent_comment_id" VARCHAR,
  "last_modify_ts" BIGINT,
  "like_count" VARCHAR,
  "sentiment" VARCHAR
);

Comments Fiction

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.comments_fiction
  • 1.17 MB
  • 18,680 rows
  • 14 columns
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CREATE TABLE comments_fiction (
  "comment_id" VARCHAR,
  "create_time" BIGINT,
  "ip_location" VARCHAR,
  "note_id" VARCHAR,
  "content" VARCHAR,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "sub_comment_count" BIGINT,
  "pictures" VARCHAR,
  "parent_comment_id" VARCHAR,
  "last_modify_ts" BIGINT,
  "like_count" BIGINT,
  "sentiment" VARCHAR
);

Comments Food

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.comments_food
  • 387.02 kB
  • 4,374 rows
  • 14 columns
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CREATE TABLE comments_food (
  "comment_id" VARCHAR,
  "create_time" BIGINT,
  "ip_location" VARCHAR,
  "note_id" VARCHAR,
  "content" VARCHAR,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "sub_comment_count" BIGINT,
  "pictures" VARCHAR,
  "parent_comment_id" VARCHAR,
  "last_modify_ts" BIGINT,
  "like_count" BIGINT,
  "sentiment" VARCHAR
);

Comments Food 2

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.comments_food_2
  • 540.4 kB
  • 8,711 rows
  • 14 columns
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CREATE TABLE comments_food_2 (
  "comment_id" VARCHAR,
  "create_time" BIGINT,
  "ip_location" VARCHAR,
  "note_id" VARCHAR,
  "content" VARCHAR,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "sub_comment_count" DOUBLE,
  "pictures" VARCHAR,
  "parent_comment_id" VARCHAR,
  "last_modify_ts" DOUBLE,
  "like_count" VARCHAR,
  "sentiment" VARCHAR
);

Comments Food Additional

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.comments_food_additional
  • 227.94 kB
  • 1,944 rows
  • 14 columns
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CREATE TABLE comments_food_additional (
  "comment_id" VARCHAR,
  "create_time" BIGINT,
  "ip_location" VARCHAR,
  "note_id" VARCHAR,
  "content" VARCHAR,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "sub_comment_count" BIGINT,
  "pictures" VARCHAR,
  "parent_comment_id" VARCHAR,
  "last_modify_ts" BIGINT,
  "like_count" BIGINT,
  "sentiment" VARCHAR
);

Comments Literature

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.comments_literature
  • 563.84 kB
  • 8,489 rows
  • 14 columns
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CREATE TABLE comments_literature (
  "comment_id" VARCHAR,
  "create_time" BIGINT,
  "ip_location" VARCHAR,
  "note_id" VARCHAR,
  "content" VARCHAR,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "sub_comment_count" BIGINT,
  "pictures" VARCHAR,
  "parent_comment_id" VARCHAR,
  "last_modify_ts" BIGINT,
  "like_count" BIGINT,
  "sentiment" VARCHAR
);

Comments Sport

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.comments_sport
  • 1.03 MB
  • 8,394 rows
  • 14 columns
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CREATE TABLE comments_sport (
  "comment_id" VARCHAR,
  "create_time" BIGINT,
  "ip_location" VARCHAR,
  "note_id" VARCHAR,
  "content" VARCHAR,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "sub_comment_count" DOUBLE,
  "pictures" VARCHAR,
  "parent_comment_id" VARCHAR,
  "last_modify_ts" DOUBLE,
  "like_count" VARCHAR,
  "sentiment" VARCHAR
);

Comments Sport Additional

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.comments_sport_additional
  • 82.74 kB
  • 1,732 rows
  • 14 columns
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CREATE TABLE comments_sport_additional (
  "comment_id" VARCHAR,
  "create_time" DOUBLE,
  "ip_location" VARCHAR,
  "note_id" VARCHAR,
  "content" VARCHAR,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "sub_comment_count" DOUBLE,
  "pictures" VARCHAR,
  "parent_comment_id" VARCHAR,
  "last_modify_ts" DOUBLE,
  "like_count" DOUBLE,
  "sentiment" VARCHAR
);

Comments Technological Development

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.comments_technological_development
  • 122.16 kB
  • 1,343 rows
  • 14 columns
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CREATE TABLE comments_technological_development (
  "comment_id" VARCHAR,
  "create_time" BIGINT,
  "ip_location" VARCHAR,
  "note_id" VARCHAR,
  "content" VARCHAR,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "sub_comment_count" BIGINT,
  "pictures" VARCHAR,
  "parent_comment_id" VARCHAR,
  "last_modify_ts" BIGINT,
  "like_count" VARCHAR,
  "sentiment" VARCHAR
);

Comments Technology Outlook

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.comments_technology_outlook
  • 597.45 kB
  • 5,237 rows
  • 14 columns
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CREATE TABLE comments_technology_outlook (
  "comment_id" VARCHAR,
  "create_time" BIGINT,
  "ip_location" VARCHAR,
  "note_id" VARCHAR,
  "content" VARCHAR,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "sub_comment_count" BIGINT,
  "pictures" VARCHAR,
  "parent_comment_id" VARCHAR,
  "last_modify_ts" BIGINT,
  "like_count" BIGINT,
  "sentiment" VARCHAR
);

Post Additional

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.post_additional
  • 346.59 kB
  • 8,257 rows
  • 13 columns
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CREATE TABLE post_additional (
  "comment_id" VARCHAR,
  "create_time" VARCHAR,
  "ip_location" VARCHAR,
  "note_id" VARCHAR,
  "content" VARCHAR,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "sub_comment_count" DOUBLE,
  "pictures" VARCHAR,
  "parent_comment_id" VARCHAR,
  "last_modify_ts" DOUBLE,
  "like_count" DOUBLE
);

Post Advertising Planning

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.post_advertising_planning
  • 706.61 kB
  • 8,343 rows
  • 13 columns
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CREATE TABLE post_advertising_planning (
  "comment_id" VARCHAR,
  "create_time" VARCHAR,
  "ip_location" VARCHAR,
  "note_id" VARCHAR,
  "content" VARCHAR,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "sub_comment_count" DOUBLE,
  "pictures" VARCHAR,
  "parent_comment_id" VARCHAR,
  "last_modify_ts" DOUBLE,
  "like_count" DOUBLE
);

Post Brand Marketing

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.post_brand_marketing
  • 345.72 kB
  • 3,878 rows
  • 13 columns
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CREATE TABLE post_brand_marketing (
  "comment_id" VARCHAR,
  "create_time" VARCHAR,
  "ip_location" VARCHAR,
  "note_id" VARCHAR,
  "content" VARCHAR,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "sub_comment_count" VARCHAR,
  "pictures" VARCHAR,
  "parent_comment_id" VARCHAR,
  "last_modify_ts" VARCHAR,
  "like_count" VARCHAR
);

Post Car

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.post_car
  • 538.14 kB
  • 539 rows
  • 20 columns
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CREATE TABLE post_car (
  "note_id" VARCHAR,
  "type" VARCHAR,
  "title" VARCHAR,
  "desc" VARCHAR,
  "video_url" VARCHAR,
  "time" BIGINT,
  "last_update_time" BIGINT,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "liked_count" VARCHAR,
  "collected_count" VARCHAR,
  "comment_count" BIGINT,
  "share_count" VARCHAR,
  "ip_location" VARCHAR,
  "image_list" VARCHAR,
  "tag_list" VARCHAR,
  "last_modify_ts" BIGINT,
  "note_url" VARCHAR,
  "source_keyword" VARCHAR
);

Post Drawing

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.post_drawing
  • 116.32 kB
  • 500 rows
  • 20 columns
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CREATE TABLE post_drawing (
  "note_id" VARCHAR,
  "type" VARCHAR,
  "title" VARCHAR,
  "desc" VARCHAR,
  "video_url" VARCHAR,
  "time" BIGINT,
  "last_update_time" BIGINT,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "liked_count" VARCHAR,
  "collected_count" VARCHAR,
  "comment_count" BIGINT,
  "share_count" BIGINT,
  "ip_location" VARCHAR,
  "image_list" VARCHAR,
  "tag_list" VARCHAR,
  "last_modify_ts" BIGINT,
  "note_url" VARCHAR,
  "source_keyword" VARCHAR
);

Post Fashion

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.post_fashion
  • 492.91 kB
  • 620 rows
  • 20 columns
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CREATE TABLE post_fashion (
  "note_id" VARCHAR,
  "type" VARCHAR,
  "title" VARCHAR,
  "desc" VARCHAR,
  "video_url" VARCHAR,
  "time" BIGINT,
  "last_update_time" BIGINT,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "liked_count" VARCHAR,
  "collected_count" VARCHAR,
  "comment_count" VARCHAR,
  "share_count" VARCHAR,
  "ip_location" VARCHAR,
  "image_list" VARCHAR,
  "tag_list" VARCHAR,
  "last_modify_ts" BIGINT,
  "note_url" VARCHAR,
  "source_keyword" VARCHAR
);

Post Fiction

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.post_fiction
  • 106.45 kB
  • 200 rows
  • 20 columns
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CREATE TABLE post_fiction (
  "note_id" VARCHAR,
  "type" VARCHAR,
  "title" VARCHAR,
  "desc" VARCHAR,
  "video_url" VARCHAR,
  "time" BIGINT,
  "last_update_time" BIGINT,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "liked_count" VARCHAR,
  "collected_count" VARCHAR,
  "comment_count" BIGINT,
  "share_count" BIGINT,
  "ip_location" VARCHAR,
  "image_list" VARCHAR,
  "tag_list" VARCHAR,
  "last_modify_ts" BIGINT,
  "note_url" VARCHAR,
  "source_keyword" VARCHAR
);

Post Food

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.post_food
  • 213.48 kB
  • 340 rows
  • 20 columns
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CREATE TABLE post_food (
  "note_id" VARCHAR,
  "type" VARCHAR,
  "title" VARCHAR,
  "desc" VARCHAR,
  "video_url" VARCHAR,
  "time" BIGINT,
  "last_update_time" BIGINT,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "liked_count" VARCHAR,
  "collected_count" VARCHAR,
  "comment_count" BIGINT,
  "share_count" BIGINT,
  "ip_location" VARCHAR,
  "image_list" VARCHAR,
  "tag_list" VARCHAR,
  "last_modify_ts" BIGINT,
  "note_url" VARCHAR,
  "source_keyword" VARCHAR
);

Post Food 2

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.post_food_2
  • 143.32 kB
  • 280 rows
  • 20 columns
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CREATE TABLE post_food_2 (
  "note_id" VARCHAR,
  "type" VARCHAR,
  "title" VARCHAR,
  "desc" VARCHAR,
  "video_url" VARCHAR,
  "time" BIGINT,
  "last_update_time" BIGINT,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "liked_count" BIGINT,
  "collected_count" BIGINT,
  "comment_count" BIGINT,
  "share_count" BIGINT,
  "ip_location" VARCHAR,
  "image_list" VARCHAR,
  "tag_list" VARCHAR,
  "last_modify_ts" BIGINT,
  "note_url" VARCHAR,
  "source_keyword" VARCHAR
);

Post Food Additional

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.post_food_additional
  • 167.45 kB
  • 200 rows
  • 20 columns
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CREATE TABLE post_food_additional (
  "note_id" VARCHAR,
  "type" VARCHAR,
  "title" VARCHAR,
  "desc" VARCHAR,
  "video_url" VARCHAR,
  "time" BIGINT,
  "last_update_time" BIGINT,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "liked_count" VARCHAR,
  "collected_count" VARCHAR,
  "comment_count" BIGINT,
  "share_count" BIGINT,
  "ip_location" VARCHAR,
  "image_list" VARCHAR,
  "tag_list" VARCHAR,
  "last_modify_ts" BIGINT,
  "note_url" VARCHAR,
  "source_keyword" VARCHAR
);

Post Literature

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.post_literature
  • 166.65 kB
  • 180 rows
  • 20 columns
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CREATE TABLE post_literature (
  "note_id" VARCHAR,
  "type" VARCHAR,
  "title" VARCHAR,
  "desc" VARCHAR,
  "video_url" VARCHAR,
  "time" BIGINT,
  "last_update_time" BIGINT,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "liked_count" VARCHAR,
  "collected_count" BIGINT,
  "comment_count" BIGINT,
  "share_count" BIGINT,
  "ip_location" VARCHAR,
  "image_list" VARCHAR,
  "tag_list" VARCHAR,
  "last_modify_ts" BIGINT,
  "note_url" VARCHAR,
  "source_keyword" VARCHAR
);

Post Sport

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.post_sport
  • 199.03 kB
  • 320 rows
  • 20 columns
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CREATE TABLE post_sport (
  "note_id" VARCHAR,
  "type" VARCHAR,
  "title" VARCHAR,
  "desc" VARCHAR,
  "video_url" VARCHAR,
  "time" BIGINT,
  "last_update_time" BIGINT,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "liked_count" VARCHAR,
  "collected_count" VARCHAR,
  "comment_count" VARCHAR,
  "share_count" BIGINT,
  "ip_location" VARCHAR,
  "image_list" VARCHAR,
  "tag_list" VARCHAR,
  "last_modify_ts" BIGINT,
  "note_url" VARCHAR,
  "source_keyword" VARCHAR
);

Post Sport Additional

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.post_sport_additional
  • 156.89 kB
  • 440 rows
  • 20 columns
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CREATE TABLE post_sport_additional (
  "note_id" VARCHAR,
  "type" VARCHAR,
  "title" VARCHAR,
  "desc" VARCHAR,
  "video_url" VARCHAR,
  "time" BIGINT,
  "last_update_time" BIGINT,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "liked_count" BIGINT,
  "collected_count" BIGINT,
  "comment_count" BIGINT,
  "share_count" VARCHAR,
  "ip_location" VARCHAR,
  "image_list" VARCHAR,
  "tag_list" VARCHAR,
  "last_modify_ts" BIGINT,
  "note_url" VARCHAR,
  "source_keyword" VARCHAR
);

Post Technological Development

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.post_technological_development
  • 139.26 kB
  • 100 rows
  • 20 columns
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CREATE TABLE post_technological_development (
  "note_id" VARCHAR,
  "type" VARCHAR,
  "title" VARCHAR,
  "desc" VARCHAR,
  "video_url" VARCHAR,
  "time" BIGINT,
  "last_update_time" BIGINT,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "liked_count" VARCHAR,
  "collected_count" BIGINT,
  "comment_count" BIGINT,
  "share_count" BIGINT,
  "ip_location" VARCHAR,
  "image_list" VARCHAR,
  "tag_list" VARCHAR,
  "last_modify_ts" BIGINT,
  "note_url" VARCHAR,
  "source_keyword" VARCHAR
);

Post Technology Outlook

@kaggle.yuanchunhong_xiaohongshu_aigc_comments_including_postsdataset.post_technology_outlook
  • 231.16 kB
  • 220 rows
  • 20 columns
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CREATE TABLE post_technology_outlook (
  "note_id" VARCHAR,
  "type" VARCHAR,
  "title" VARCHAR,
  "desc" VARCHAR,
  "video_url" VARCHAR,
  "time" BIGINT,
  "last_update_time" BIGINT,
  "user_id" VARCHAR,
  "nickname" VARCHAR,
  "avatar" VARCHAR,
  "liked_count" VARCHAR,
  "collected_count" VARCHAR,
  "comment_count" BIGINT,
  "share_count" BIGINT,
  "ip_location" VARCHAR,
  "image_list" VARCHAR,
  "tag_list" VARCHAR,
  "last_modify_ts" BIGINT,
  "note_url" VARCHAR,
  "source_keyword" VARCHAR
);

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