Add news section

Author: RSTZZZ

_config.yml

@@ -142,6 +142,17 @@ defaults:
         - no-sidebar
       author_profile: false
 
+    # _posts/news
+  - scope:
+      path: _posts/news
+      type: posts
+    values:
+      layout: single
+      classes:
+        - no-sidebar
+      author_profile: false  
+  
+
   # _pages/profiles
   - scope:
       path: "_pages/profiles"

_data/navigation.yml

@@ -18,7 +18,7 @@ main:
       - page: "About the Lab"
         url: /about/
       - page: "News"
-        url: /
+        url: /news/
       - page: "People"
         url: /people/
       - page: "Teaching"

_pages/news.md

@@ -0,0 +1,14 @@
+---
+title: News
+layout: publication
+classes:
+    - no-sidebar
+    - wide
+permalink: /news/
+taxonomy: News
+
+---
+
+Complex Data Lab latest news and annoucements
+
+

_posts/news/2025-07-01-Social_Sim_2025.md

@@ -0,0 +1,11 @@
+---
+title: "Social Sim'25"
+venue: Social Simulation with LLMs has been accepted at COLM 2025!
+names: Zachary Yang, Kellin Pelrine, Maximillian Puelma Touzel, Dan Zhao, Jean-Francois Godbout, Petter Törnberg, Reihaneh Rabbany, William Cunningham
+author: Zachary Yang
+categories: News
+thumbnail: "assets/images/news/social_sim.jfif"
+---
+
+
+We’re pleased to announce that our workshop SocialSim’25: Social Simulations with LLMs has been accepted at COLM 2025, taking place in Montreal on October 10. This workshop brings together work on modeling and simulating social media behavior using LLMs, with a focus on agent-based simulations, behavioral evaluation, and online harms. For more information, please refer to [here](https://sites.google.com/view/social-sims-with-llms)

_posts/papers/2024-01-01-2024.eurali-1.8.md

@@ -10,7 +10,7 @@ link: https://www.semanticscholar.org/paper/05d76a00dd42fd5e75a7222d4479d2a35608
 author: Sahar Omidi Shayegan
 categories: 
 - Publications
-- ideology-and-polarization
+- poli-sci
 excerpt: "While LLMs have demonstrated how effective they can be for tasks in the English language, such as detecting social media users’ political ideology, their performance in other languages remains understudied. We contribute to this area of research by fine-tuning smaller LLMs to identify hyperpartisans in Persian social media, and compare the results to those from open-source and commercial models. "
 
 ---