| | --- |
| | pretty_name: "Social Vision and Language Dataset (SVLD)" |
| | license: "other" |
| | language: |
| | - en |
| | tags: |
| | - multimodal |
| | - vision-language |
| | - social-media |
| | - image |
| | - video |
| | - text |
| | - comment-trees |
| | - popularity-prediction |
| | - arxiv:2006.08335 |
| | - datasets |
| | task_categories: |
| | - image-text-to-text |
| | - image-to-text |
| | - video-text-to-text |
| | - image-classification |
| | - text-classification |
| | - visual-question-answering |
| | - tabular-regression |
| | size_categories: |
| | - 1M<n<10M |
| | --- |
| | |
| | # Social Vision and Language Dataset (SVLD) |
| |
|
| | **Original Paper:** *A Dataset and Benchmarks for Multimedia Social Analysis* (2020) |
| | **Authors:** Bofan Xue, David Chan, John Canny |
| | **Institution:** University of California, Berkeley |
| |
|
| | --- |
| |
|
| | ## 📌 Overview |
| |
|
| | The **Social Vision and Language Dataset (SVLD)** is a large-scale multimodal |
| | social media dataset designed to support research in: |
| |
|
| | - Vision–language modeling |
| | - Multimodal fusion |
| | - Social signal prediction |
| | - Comment-tree modeling |
| | - Temporal social dynamics |
| | - Content popularity prediction |
| |
|
| | SVLD combines **images, videos, text, social engagement signals, and full comment trees** within the same context, enabling joint modeling across modalities in realistic, in-the-wild social media settings. |
| |
|
| | --- |
| |
|
| | ## 📦 Current Release (S3 Shard Edition) |
| |
|
| | The dataset is currently distributed as: |
| |
|
| | > **1961 daily shards** |
| |
|
| | Each shard corresponds approximately to one day of collected data. |
| |
|
| | ### ⚠ Important Notice |
| |
|
| | Due to long-term storage issues and partial data corruption: |
| |
|
| | - This release **may not contain the full original dataset** |
| | - Some days, posts, media files, or metadata may be missing |
| | - Total dataset size may vary |
| |
|
| | Researchers are strongly encouraged to: |
| |
|
| | - Recompute dataset statistics locally |
| | - Avoid assuming counts from the original publication |
| | - Design pipelines that tolerate partial or missing data |
| |
|
| | --- |
| |
|
| | ## 🧩 Dataset Structure |
| |
|
| | ### Each Post May Contain |
| |
|
| | - One or more images |
| | - One or more videos |
| | - Optional per-media descriptions |
| | - A natural language title |
| | - User-provided tags |
| | - Social signals (upvotes, downvotes, favorites, views) |
| | - Timestamp |
| | - A full comment forest |
| |
|
| | ### Each Comment May Contain |
| |
|
| | - Text |
| | - Images |
| | - GIFs or videos |
| | - Recursive replies (tree structure) |
| |
|
| | --- |
| |
|
| | ## 🎯 Modalities |
| |
|
| | SVLD supports research across: |
| |
|
| | - **Images** (posts + comments) |
| | - **Videos** (posts + comments) |
| | - **Text** (titles, descriptions, comments) |
| | - **Social Metrics** (votes, favorites, views) |
| | - **Tags** (user-generated) |
| | - **Tree Structure** (comment forests) |
| | - **Temporal Data** (timestamps) |
| |
|
| | --- |
| |
|
| | ## 🔬 Research Directions |
| |
|
| | SVLD enables work in: |
| |
|
| | - Multimodal fusion architectures |
| | - Image/video + language modeling |
| | - Popularity and engagement prediction |
| | - Social dynamics modeling |
| | - Tag and metadata prediction |
| | - Comment tree reasoning |
| | - Temporal distribution analysis |
| | - Multimodal retrieval |
| | - Content moderation research |
| |
|
| | --- |
| |
|
| | ## ⚙ Data Quality Notes |
| |
|
| | - Some media files may be unavailable |
| | - Some shards may be incomplete |
| | - Social metrics reflect snapshot-at-scrape time |
| | - Engagement distributions are heavily long-tailed |
| | - Content reflects real-world social media (unfiltered, in-the-wild) |
| |
|
| | --- |
| |
|
| | ## 📖 Citation |
| |
|
| | If you use SVLD, please cite: |
| |
|
| | > Xue, B., Chan, D., & Canny, J. (2020). |
| | > *A Dataset and Benchmarks for Multimedia Social Analysis.* |
| | > arXiv:2006.08335 |
| |
|
| | --- |
| |
|
| | ## 📜 License & Usage |
| |
|
| | This dataset is intended for **academic research use only**. |
| | Users are responsible for complying with platform terms and ethical research standards. |
