Update China Diplomacy project with full content and metadata

Author: 李林颖

content/projects/china-diplomacy/index.md

@@ -1,20 +1,47 @@
 ---
 title: "Speaking as Barometer: How Chinese Diplomats' Words Reflect the Sino-American Relationship"
-summary: "Sentiment and Word Cloud analysis of Chinese Foreign Ministry briefings (2002–2022)."
+summary: "A data-driven journalism project analyzing 20 years of Chinese Foreign Ministry press conferences using Sentiment Analysis in R."
 tags:
 - NLP
 - Sentiment Analysis
+- R
+- Political Economy
 - China Studies
 date: "2023-01-15T00:00:00Z"
 
+# Links
+links:
+- name: Original Blog
+  url: https://pwiweb.uzh.ch/wordpress/blog/2023/08/21/speaking-as-barometer-how-chinese-diplomats-words-reflect-the-sino-american-relationship/
+  icon_pack: fas
+  icon: globe
+- name: R Code
+  url: https://github.com/LinyingL/Datenjournalismus/blob/main/DDJ2.R
+  icon_pack: fab
+  icon: github
+
 image:
-  caption: Word Cloud Visualization
+  caption: "Word Cloud Analysis"
   focal_point: Smart
 ---
 
-This project applied dictionary-based **Sentiment Analysis** to two decades of Chinese Foreign Ministry press briefings focused on "America".
+*Originally published as a featured blog post at IPZ/UZH.*
+
+### Overview
+From trade to human rights, the superpowers are battling on almost all topics since Trump. Through **sentimental analysis** of Chinese Foreign Ministry spokespersons‘ responses on U.S. topics from **2002 to 2022**, this project observes the changing dynamics of the world's most important bilateral relations.
+
+### Methodology
+- **Dataset**: Ministry of Foreign Affairs Press Conferences Corpus (2002-2022).
+- **Tools**: Analyzed in **R** using the `quanteda` and `zoo` packages.
+- **Sentiment Scoring**: Used the Bing dictionary (Liu & Hu, 2004) and the formula: $sentiment = log((positive + 0.5)/(negative + 0.5))$.
+- **Visualisation**: Interactive plots generated via `Plotly` and Word Clouds for key diplomatic crises.
 
-### Key Methods:
-- **Sentiment Analysis**: Tracking emotional tones across different diplomatic eras.
-- **Data Visualization**: Created **Word Clouds** to highlight key terms during the Trade Conflict and North Korean Nuclear Crisis.
-- **Impact**: Published as a featured blog post on the department's website.
+### Key Findings
+1. **The Era of Constructive Cooperation (2002-2016)**: Diplomatic language remained largely positive, peaking during events like the 2008 Beijing Olympics, despite occasional friction over trade and regional security.
+2. **The Shift to Strategic Competition (2017-2022)**: A sharp decline in sentiment following the 2018 Trade War and the COVID-19 pandemic.
+3. **The "Wolf Warrior" Turn**: Notable shifts in rhetoric style under different spokespersons (e.g., Zhao Lijian), reflecting a more confrontational diplomatic stance.
+
+> "The human language contains personal attitudes and sentiments. In the diplomatic field, these are often suppressed, but press conferences reveal genuine emotions through on-the-spot reactions."
+
+---
+*For the full interactive experience and detailed data charts, please visit the original blog post linked above.*