Update README.md

README.md

@@ -3,10 +3,10 @@ MASH: A Multiplatform and Multimodal Annotated Dataset for Societal Impact of Hu
 license: cc-by-4.0
 tags:
 - climate
+- disaster
 - social-media
 - hurricane
 - TikTok
-- Twitter
 - YouTube
 - Reddit
 - multimodal
@@ -18,7 +18,7 @@ size_categories:
 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. 
+  We present a Multiplatform Annotated Dataset for Societal Impact of Hurricane (MASH) that includes 59,607 relevant social media data posts from Reddit, 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. 
@@ -45,7 +45,7 @@ modalities:
 ---
 # MASH: A Multiplatform and Multimodal Annotated Dataset for Societal Impact of Hurricane
 
-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**. 
+We present a Multiplatform Annotated Dataset for Societal Impact of Hurricane (MASH) that includes **59,607** relevant social media data posts from **Reddit**, **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 (text, images, and videos), providing a rich labeled dataset for in-depth analysis.
 
 The dataset is also complemented by an [Online Analytics Platform](https://hurricane.web.illinois.edu/) 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.
@@ -61,7 +61,6 @@ This dataset includes four annotation files:
 
 	• reddit_anno_publish.csv
 	• tiktok_anno_publish.csv
-	• twitter_anno_publish.csv
 	• youtube_anno_publish.csv
 
 Each file contains post IDs and corresponding annotations on three dimensions:
@@ -70,7 +69,6 @@ Humanitarian Classes, Bias Classes, and Information Integrity Classes.
 To protect user privacy, only post IDs are released. We recommend retrieving the full post content via the official APIs of each platform, in accordance with their respective terms of service.
 - [Reddit API](https://www.reddit.com/dev/api)  
 - [TikTok API](https://developers.tiktok.com/products/research-api)  
-- [X/Twitter API](https://developer.x.com/en/docs/x-api)  
 - [YouTube API](https://developers.google.com/youtube/v3)
 
 ## Humanitarian Classes
@@ -127,4 +125,4 @@ Each post is also annotated with a single information integrity class, represent
         primaryClass={cs.SI},
         url={https://arxiv.org/abs/2509.23627}}
   
-ZENODO DOI: [10.5281/zenodo.15401479](https://zenodo.org/records/15401479)
+ZENODO DOI: [10.5281/zenodo.15401479](https://doi.org/10.5281/zenodo.15401479)