What it is
Source: My own words (15 October 2026) and the LSE USAPP post of 25 November 2024. Date: My internship, September to December 2024; the survey, October to November 2024. Scope: A research analysis project and my part in it. The respondent and country counts are the project’s figures, not my outcome.
YouSay-WeSay is a research analysis project at Deakin University on global perceptions of the 2024 US presidential election. I was its analyst, as a research intern at Deakin’s Applied Artificial Intelligence Institute (A²I²) from September to December 2024.
According to the authors’ write-up, its online poll ran from early October to 5 November 2024 and drew 1,082 respondents from 39 countries. Project
What it does
- The questions. Respondents said who they thought would win and who they would prefer to win, and chose from 10 policy fields. Project
- Countries compared. Answers compared across respondents’ countries.
How it is built
I built visualisations in Python, with matplotlib and seaborn, and in JavaScript. A²I²’s news post of 4 October 2024 says the institute’s computer scientists and software engineers provided platform development and data analysis support. The authors note that the sample was not recruited to be perfectly representative.
Stack. Python, matplotlib, seaborn, JavaScript
Where it stands
The authors’ write-up, by Zim Nwokora, Russell Kennedy and Rajesh Vasa, appeared on the London School of Economics USAPP blog on 25 November 2024 and acknowledges me among the project’s student interns (spelt “Adhi Ajit”).
My part
I was the analyst. I processed the multi-country survey data and built visualisations of global perceptions of the election. The poll, the write-up and the analysis in it are the authors’.
YouSay-WeSay
The stages of the project’s research analysis, drawn one by one: the responses, their preparation, the comparison across countries, the visualisations and the authors’ write-up. I was the analyst: I processed the multi-country survey data and built visualisations in Python (matplotlib, seaborn) and JavaScript.
The project’s figure, not my outcome. The survey ran Oct to Nov 2024, during my internship, Sep to Dec 2024. Project
- Responses
The project’s online poll, October to November 2024: who will win the US election, and who they would prefer to win.
- Prepare
The multi-country survey data, which I processed and made ready for analysis.
- Analyse
Answers compared across countries, the multi-country survey analysis. I was the analyst.
- Visualise
Visualisations of the results, including those I built in Python (matplotlib, seaborn) and JavaScript.
- Publish
The authors’ write-up on the LSE USAPP blog, 25 November 2024, acknowledging the student interns.
Claim
Source: LSE USAPP blog, 25 Nov 2024. Date: 2024-11-25. Scope: The project’s figure, not my outcome. The survey ran in October and November 2024, during my internship, which ran from September to December 2024.
YouSay-WeSay is a Deakin University survey project on the 2024 US election, run across many countries. The survey drew participation from 1082 respondents from 39 countries. Project
I am acknowledged as a student intern in the project’s write-up on the LSE USAPP blog, by Zim Nwokora, Russell Kennedy and Rajesh Vasa, published on 25 November 2024. The figure is the project’s, not mine.
My part: as a research intern at Deakin’s Applied Artificial Intelligence Institute from September to December 2024, I was the analyst on the project. I processed the multi-country survey data and built visualisations in Python (matplotlib, seaborn) and JavaScript. Reported
The dates: my internship ran from September to December 2024, the public survey ran in October and November 2024, and the post appeared on 25 November 2024. My part is described in my own words; the acknowledgement and the figures are from the post.
Method
Source: The LSE USAPP post; my own words. Date: Sep to Dec 2024 (my part); Oct to Nov 2024 (the survey). Scope: Which parts were mine. The figure draws the stages of the project’s research analysis, from the LSE write-up and my own words; it is a diagram, not the project’s own material.
The figure draws the stages of the project’s research analysis: the survey’s responses, their preparation for analysis, the comparison across countries, the visualisations, and the authors’ write-up. It is drawn here as method, from the LSE write-up and my own words, not lifted from the project.
My part: I was the analyst. I processed the multi-country survey data and built visualisations in Python (matplotlib, seaborn) and JavaScript. The poll, the write-up and the analysis in it are the authors’.
Raw
Source: LSE USAPP blog. Date: 2024-11-25, verified 2026-10-09. Scope: Two sentences quoted from the post, verbatim.
The excerpt
The 2024 Elections: Outside the US, most people were not predicting a Donald Trump win. Zim Nwokora, Russell Kennedy and Rajesh Vasa (Deakin University; Vasa leads research with the Applied Artificial Intelligence Institute). LSE USAPP blog, 25 November 2024.
The authors would like to acknowledge the valuable support of the YSWS student interns: Adhi Ajit, Tia Kapoor and Dat Tu.
On the survey’s reach, the post says it “drew participation from 1082 respondents from 39 countries”. Project
Read the post: blogs.lse.ac.uk, 25 November 2024. The spelling “Adhi Ajit” is the post’s.
