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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
  • 308.96 KB
  • 7744 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
  • 606.6 KB
  • 7514 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
  • 313.79 KB
  • 3739 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
  • 1.09 MB
  • 10560 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
  • 442.3 KB
  • 9246 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
  • 925.86 KB
  • 9453 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
  • 1.12 MB
  • 18680 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
  • 377.95 KB
  • 4374 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
  • 527.74 KB
  • 8711 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
  • 222.6 KB
  • 1944 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
  • 550.63 KB
  • 8489 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
  • 1004.38 KB
  • 8394 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
  • 80.8 KB
  • 1732 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
  • 119.29 KB
  • 1343 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
  • 583.44 KB
  • 5237 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
  • 338.47 KB
  • 8257 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
  • 690.04 KB
  • 8343 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
  • 337.61 KB
  • 3878 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
  • 525.52 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
  • 113.6 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
  • 481.36 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
  • 103.96 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
  • 208.48 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
  • 139.96 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
  • 163.53 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
);

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