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README.md
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---
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language:
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- zh
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- en
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pretty_name: TopicVid
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---
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# TopicVid Dataset
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This dataset provides structured metadata, content features, and a heterogeneous graph related to short-video topics and subtopics. It is designed for tasks such as topic analysis, audience interaction modeling, peak prediction, and research on graph neural networks or graph retrieval.
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---
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## Contents
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- `available_dataset_with_subtopic.json` — Processed structured raw data of short video content and interaction statistics about topics.
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- `comment.npy` — Comment features.
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- `content.npy` — Content features.
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- `desc.npy` — Description features.
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- `heterogeneous_graph.pkl` — Heterogeneous graph file.
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- `title.npy` — Title features.
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- `topic.npy` — Topic embeddings.
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- `video.npy` — Video features.
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---
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## Data Structure
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### 1) `available_dataset_with_subtopic.json`
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This file contains the raw data of short video content and interaction statistics.
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Fields:
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- `url` (string) — Direct link to the video on the platform.
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- `desc` (string) — Description text of the video content.
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- `title` (string) — Title of the video post.
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- `content` (string) — Additional text content; may be empty.
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- `user_id` (string) — Unique identifier of the publishing user.
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- `duration` (integer) — Video duration in seconds.
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- `platform` (string) — Source platform name (e.g., Douyin, Kuaishou).
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- `post_create_time` (string) — Time of publication in "YYYY-MM-DD HH:MM:SS" format.
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- `topic` (string) — Main topic associated with the video.
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- `subtopic` (string) — Numbered subcategory under the main topic.
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- `time_frames` (dict) — Interaction statistics recorded at different dates.
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- Key: Date in "YYYY-MM-DD" format
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- Value: Dictionary with fields:
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- `fans_count` — Number of followers
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- `like_count` — Number of likes
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- `view_count` — Number of views
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- `share_count` — Number of shares
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- `collect_count` — Number of collections
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- `comment_count` — Number of comments
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- `comments` (dict) — Collection of user comments.
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- Key: Comment index (string)
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- Value: Dictionary with fields:
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- `comment_user_id` — Commenting user ID
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- `comment_nickname` — Commenting user's display name
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- `comment_content` — Comment text
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- `comment_time` — Time of comment
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- `ip_address` — IP location of the commenting user
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### 2) `*.npy`
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Numpy arrays containing preprocessed embeddings or feature vectors.
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### 3) `heterogeneous_graph.pkl`
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A serialized Python object containing:
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- Node types and indices
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- Edge types and lists
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- Labels information is available at [link](https://github.com/chensh911/TLGM/blob/main/data/subtopic_label.csv)
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