Update README.md

README.md

@@ -3,16 +3,39 @@ MASH: A Multiplatform Annotated Dataset for Societal Impact of Hurricane
 license: cc-by-4.0
 tags:
 - climate
-- socialmedia
+- social-media
 - hurricane
 - TikTok
 - Twitter
 - YouTube
 - Reddit
 - multimodal
+- misinformation
+- humanitarian
+- bias
 size_categories:
 - 10K<n<100K
 pretty_name: Multiplatform Annotated Dataset for Societal Impact of Hurricane
+language: en
+description: >
+  We present a Multiplatform Annotated Dataset for Societal Impact of Hurricane (MASH) that includes 98,662 relevant social media data posts from Reddit, X, TikTok, and YouTube. 
+  In addition, all relevant posts are annotated on three dimensions: Humanitarian Classes, Bias Classes, and Information Integrity Classes in a multi-modal approach that considers both textual and visual content, providing a rich labeled dataset for in-depth analysis.
+  The dataset is also complemented by an Online Analytics Platform that not only allows users to view hurricane-related posts and articles, but also explores high-frequency keywords, user sentiment, and the locations where posts were made.
+  To our best knowledge, MASH is the first large-scale, multi-platform, multimodal, and multi-dimensionally annotated hurricane dataset. 
+  We envision that MASH can contribute to the study of hurricanes' impact on society, such as disaster severity classification, event detections, public sentiment analysis, and bias identification.
+dataset_type:
+  - multimodal
+  - text
+  - image
+  - video
+annotations_creators:
+- expert-annotated
+- LLM
+- mix
+task_categories:
+  - text-classification
+  - image-classification
+  - video-classification
 ---
 # MASH: A Multiplatform Annotated Dataset for Societal Impact of Hurricane