Hello, my name is Zoe Meers and I work in data analytics at Canva. I previously specialized in data visualization with a substantive focus on US politics. In my spare time, I develop open-source statistical software in R.

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Data visualization portfolio

The wildcards that could help Donald Trump dodge electoral humiliation in the 2020 US presidential election

COVID-19: Australia and the United States by the numbers

Isolated AgTech in Australia? A social network analysis of an innovative sector

Public opinion in the United States and Australia compared

Women candidates in the midterm elections

Midterm election seats in play

A year of turmoil, but Trump’s voters are with him

Failure to launch: Australia, the United States and the threat of inefficient innovation

R Packages

I am a co-author on two R packages that are available for download on CRAN.

  • ggparliament for visualizing parliaments and legislatures using ggplot2 syntax. CRAN StatusDownloads

  • readabs for pulling data from the Australian Bureau of Statistics API (currently maintained by Matt Cowgill). CRAN StatusDownloads

I have also made an internal workplace-wide packages for statistical analysis and visualization, and have contributed to other widely used R packages including pscl.

Talks

A how-to for graphs and data viz in Canva.
Oct 20, 2021 12:00 AM Sydney, Australia
Slides Video

On data visualization and politics.
May 4, 2020 12:00 AM Melbourne, Australia
Slides

A look at the Google News Lab Fellowship and data journalism in Australia.
May 18, 2018 12:00 AM Brisbane, Australia
Slides

Publications

International Cyber Policy Centre
This report explores how the Chinese Communist Party (CCP), fringe media and pro-CCP online actors seek—sometimes in unison—to shape and influence international perceptions of the Chinese Government’s human rights abuses in Xinjiang, including through the amplification of disinformation. United States (US) based social media networks, including Twitter, Facebook and YouTube, along with Chinese-owned TikTok (owned by Chinese company ByteDance), are centre stage for this global effort.

United States Studies Centre, Univ. of Sydney
Poll-based election forecasts were widely maligned after the 2016 election, and with some justification: Trump won the election when the bulk of the polling said he would not. Forecasts based on polls performed well in 2008 and 2012, with several analysts (including one of us) correctly picking the winner in all fifty states in 2012. And yet the same methodology — using statistical models to combine poll results — did not fare nearly so well just four years later in 2016. The accurate performance of these methods in 2008 and 2012 led many analysts of 2016 polling data to incorrectly predict Trump would lose.

In the Canberra Times
Five primary elections in five US states were delayed due to the COVID-19 pandemic this week. The governors of Georgia, Kentucky, Louisiana, Maryland, and Ohio postponed upcoming elections to determine the Democratic candidate for the presidential election against President Trump in November.
See all publications

Accomplishments

50 women to follow in computational social science

SAGE Ocean Oct 2018

Google News Initiative Fellow with ABC

Google Jan 2018 – Mar 2018
Data visualization fellowship with Google HQ and the ABC Story Lab.