Wikisplash is for trending people and topics

I’m excited to share a new project I’ve just released: Wikisplash.com. It’s a web-based tool that uses Wikipedia data as a proxy for public attention – at both the global and national level.

Wikisplash is like Google Trends for who’s looking at Wikipedia pages.

Some of you know that, alongside my interest in politics, I’m also a web and software developer. I originally shared this weekend project in a group chat with colleagues via a development URL. One noted it was useful enough to deserve a proper home – so Wikisplash.com was born.

What is Wikisplash?

Wikipedia has articles on nearly every named entity – people, places, and things. Wikisplash lets you see the number of pageviews those articles have received, going back years.

Because Wikipedia links often appear at the top of Google search results, its pageview stats serve as a reasonable proxy for global search interest. This is the case not only on Wikipedia but indirectly through Google as well.

Wikisplash is for trending topics
Interest in a selection of countries in the last two years

As I’ve suggested, Google Trends does something similar though in a more limited way. Reflecting actual Google search traffic, Google Trends shows search interest only as relative percentages. Wikisplash shows absolute pageviews by date. That makes it easier to compare attention over time and across topics.

Why trending topics matter

If you work in politics, media, or marketing, you already know that attention is insight. Tracking what people are curious about helps you stay ahead of conversations.

Even though writing for SEO has become less of a newsroom priority, search interest remains a strong signal of public curiosity. Editors, strategists, and political communicators have always used trending topics as a cheat code to tap into what people care about – whether via Google or social platforms like X.

Global English Wikipedia mindshare of Donald Trump and Elon Musk

Wikisplash breaks down trending topics by recency “yesterday”, “last 7 days”, and “last 30 days”, while also doing this by country. If you really want to be specific, you can look at global trends by the language of Wikipedia (en.wikipedia.org vs fr.wikipedia.org)

I’ve been fascinated by predictive analytics for some time, for the same reason as anyone would be – getting to the future before others confers its obvious advantages. Website newsletters like Exploding Topics curate trending topics that interest its authors. Tools like Ahrefs and SEMrush are mostly used for SEO, though more are using these sites to anticipate market demand and social direction.

Snapshot of the most visited Wikipedia articles by Canadians in the last 7 days

I’ve also added easy ways to share this data and visualizations of the same. You can easily download chart images, embed them on your own website, or link to the topics on social media.

Which social media platforms dominate?

Wikispash aims to provide tools to interpret the raw data so you can come to your own conclusions and for your own purposes. I hope that it is useful for you! Tell me what you think of it on X/Twitter.

Wikisplash is for trending topics! – Wikisplash.com

Mapping the results of the 2022 Ontario Provincial Election

I just finished mapping out Doug Ford’s Progressive Conservative election win from 2022. On June 2 of that year, the voters of Ontario returned the PC leader with a majority government with 83 seats. The Progressive Conservatives defeated the Ontario Liberals led by Steven Del Duca and the Ontario NDP which was helmed by Andrea Horwath. Both defeated party leaders would move on from provincial politics and have since become the mayors of Vaughan and Hamilton, respectively.

The results of this pandemic-era election were very much similar to the 2018 provincial election – another majority for the PC under Ford – but the election saw a strenghthened mandate for the Premier. One independent candidate was elected in Haldimand–Norfolk.

This is the sixth election I’ve mapped out for the province of Ontario. You can review all of those elections here and drill down on the results of this one using the provincial map.

The mapped results of the 2022 Ontario Provincial election

Clicking/tapping on a riding will zoom you into the map for a poll-by-poll breakdown. You can dive into your own riding and find out how your neighbours voted! Hovering over ridings or neighbourhood polls will show a pie chart breakdown of the proportion of votes in a particular area. Expanding the tile at the bottom right and switching to the “Turnout” tab will show voter turnout rates on a riding level or can show poll-by-poll rates of partipation.

Scarborough Centre coloured by poll winner.

You can also use the search bar at the top of the page to search for any candidate or riding over the last 6 elections. Some candidates appear more than once and you can track their electoral history (no matter which riding they may have contested). Clicking on a riding will also show a “related content” button at the top of the page which you can use to find the results of nearby ridings. A few of those ridings are also summarized below the map.

Green party win in Guelph shaded by the strength of the Progressive Conservative vote (ironically the colour green showing strongest PC areas here). Mike Schreiner, the Green Party leader won the party’s only seat.

If you’re wondering how to take these screenshots to put these images in your own posts or tweets, click the camera at the top left of the map. This will download an image of the map.

Zooming around the map is a lot of fun. It’s vector-based, so zooming in and out is smooth and looks great.

Clicking the “Up to 2022 Provincial Election” button in the top right zooms the map out to the provincial riding context, while clicking on a riding zooms in to show the local breakdown.

A particularly strong neighbourhood poll for PC candidate Doug Ford in Etobicoke North.

I’ve integrated building footprints for all of Ontario (and Canada) into my map, so you can see grouping of houses on cul-de-sacs, apartment buildings, and in some cases even the house numbers.

NDP leader Andrea Horwath best poll in Hamilton Centre.

Visualizing these building footprints in neighbourhoods for various polls is a new feature of this iteration of these maps. I’ve also extended this feature to my previous maps (both federal and provincial). It can be useful to consider different zoning and dwelling types when appreciating party strength in a riding.

Liberal leader Steven Del Duca did not have a great showing in his riding of Vaughan–Woodbridge.

I enjoy pulling these maps together for the broader political community and to help voters further engage with our democratic process. I’ll be mapping other provincial elections as that data becomes available from the relevant provincial elections agencies.

York South–Weston showing a diversity of voting preferences throughout the riding.

Intelligence whistleblower publishes op-ed on election interference

In case you’ve been living under a rock – or locked up in a re-education centre – the Canadian political establishment has been rocked by revelations from both the Globe and Mail and Global News regarding interference in Canadian elections by the Communist Party of China.

This afternoon in the Globe, the whistleblower that formed the “backbone” of this reveal (according to an attached note from Editor-in-Chief David Walmsley) penned an op-ed explaining why they did this and what’s at stake.

Respecting the subscriber paywall, I’ll just report on the news of this op-ed (do subscribe to the Globe and Mail).

First, the whistleblower is a Liberal voter and hopes to vote Liberal again in the future. This will be an interesting point to some, as a standard (weak) defence against the facts is the allegation of partisanship. These leaks have been damaging for Justin Trudeau’s government first-and-foremost, so this will clarify some of the waters which have been muddied in the defence of the Prime Minister.

From the op-ed, we learned that the leaks were instigated as a result of inaction by supervisors, and inaction by top government officials to do anything on “the threat” which “grew in urgency” and that “serious action remained unforthcoming”. In fact, as the threat of foreign interference grew, and as elections passed, the whistleblower perceived that these warnings were only being ignored.

Additionally, serious consequences have weighed on the public servant. Worries about family, prison, career were considered but were ultimately weighed against the public interest. Further, a desire to protect any Canadian against coercion by a hostile foreign power gave weight to the whistleblower’s decision to go public – and they expect to eventually be unmasked (“if and when”) for their role in bringing this to light.

It’s important to note that as the source of these stories, this individual does not believe that the government itself would be different had there been no interference by Beijing. Furthermore, that no politician has betrayed their country via the CCP’s meddling. Finally, it is the Chinese diaspora that has borne the brunt of these manipulations and one should conclude that Canada’s institutions should protect them from such an assault.

“Knowing that while what I have done may be unlawful, I cannot say that it was wrong”

It is not known where the whistleblower works – whether at CSIS, the PCO, PMO, or another government department or agency with access to classified information.

Who is the Canadian whistleblower? For now, I get to speculate using the Archer checkpoint model for Stable Diffusion.