Paper
From official language to market-facing signal
Diplomatic Sentiment Observatory
This site presents the Diplomatic Sentiment Observatory (DSI): a three-part family of daily diplomatic sentiment indices built from official diplomatic texts. War-related, economic, and other diplomatic sentiment are treated here as parallel DSI branches that can be compared side by side.
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Citation
Please cite the paper when using this dataset
APA Style
Yang, C., Zhang, S., Kyriakou, I., & Papapostolou, N. C. (2026). When words move money: Diplomatic sentiment and international capital flows. SSRN. https://ssrn.com/abstract=6437669
Chicago Style
Yang, Cunyi, Shuchi Zhang, Ioannis Kyriakou, and Nikos C. Papapostolou. 2026. "When Words Move Money: Diplomatic Sentiment and International Capital Flows." SSRN. https://ssrn.com/abstract=6437669
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Selected branch - 30-day change
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Compared with the 30-day smoothed value 30 days earlier
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Overview
Cross-Country DSI Signal Board
Start with the full cross-country picture, then move into each country series. The headline number on each card follows the currently selected DSI branch, so you can compare the three branches across countries on the same footing.
Explorer
Index Explorer
Switch first across the three DSI branches, then choose whether to view the 7-day trend, 30-day trend, or the raw publication-day score for the selected branch.
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Method
How Diplomatic Text Becomes DSI
DSI is neither keyword counting nor one-shot sentiment scoring. It comes from cleaning official diplomatic texts, scoring them across three diplomatic dimensions, validating the results through consensus checks, and aggregating them into daily high-frequency indices.
Collect and clean official texts
The paper starts from official releases by multiple foreign ministries, including press-conference transcripts, statements, briefings, and written responses. These texts are segmented, stripped of greetings and procedural language, and reorganized into comparable daily series.
Identify sentiment in three stages
The paper scores official texts across three diplomatic dimensions: war-related, economic, and other diplomatic sentiment. Each dimension is converted into a discrete score from -3 to 3 before daily aggregation.
Run consensus checks and manual audits
To reduce misclassification, the paper repeats each judgement multiple times. Only matching results pass directly; disagreements are reviewed before moving on. The pipeline is also audited against manually labelled samples to keep the classifications close to researcher judgement.
Construct the daily index series
The paper first forms a raw score on each publication day for each DSI branch. When multiple texts appear on the same day, the raw daily value takes the lowest score observed that day rather than an average. Missing days are then forward-filled, and the 3-day, 7-day, and 30-day series are computed as rolling means on that filled daily path.
Why It Matters
What We Have Already Found in the DSI Data
Our current paper evidence is strongest on the war-related branch, but the broader DSI family is designed to support parallel work on geopolitical expectations, cross-border capital flows, market responses, and future branch-specific extensions.
It moves before conventional risk measures
Our paper finds that war-related diplomatic wording often shifts before standard geopolitical risk indicators do, making it useful for detecting changes in market expectations around escalation or de-escalation earlier.
It changes the direction of cross-border flows
In the China sample, more negative war-related diplomatic sentiment is associated with stronger capital outflow pressure. Our estimates show that a one-unit decline in China's war-related DSI corresponds to roughly a 35.6 million USD shift in daily net flows toward outflows.
It carries both safe-haven and spillover effects
Our paper also finds that more negative U.S. diplomatic sentiment is associated with stronger safe-haven demand for U.S. equities. Negative sentiment from the United Kingdom, Japan, and South Korea also spills over into the Chinese market, with clearer effects on returns and trading activity.
More value is still waiting to be found
The site exposes the raw series as well as the 7-day and 30-day smoothed versions, making it easier to extend the dataset into event studies, cross-country comparisons, asset-pricing work, and capital-flow tests.
Download
Data Downloads
This section provides a combined DSI workbook, branch-specific cross-country panels, and country-level workbooks that include all three DSI branches together with raw publication-day values and 3-day, 7-day, and 30-day smoothed series.
Supplement
Trump Indices Supplement
This bottom panel adds an actor-level signal alongside the ministry-based DSI family. It tracks Donald Trump's own cross-platform posting tone, geopolitical stance, and shock intensity across Twitter and Truth Social, and should be read as a complement to the broader DSI site rather than as a substitute for any single ministry-based DSI branch.
Coverage
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Trump Tone Index
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Trump Geopolitical Index
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Trump Shock Index
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Directed Signals
Trump Directed Sentiment by Country
This extension isolates Trump's country-targeted rhetoric across the same fourteen-country universe used elsewhere on the site. Country-directed tone and geopolitical stance are only defined on dates with a material mention of that country, while attention tracks how intensely the country is being referenced.
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Candidate texts
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