The silver lining to the cloud of increasing search awfulness is that it’s forced me to think deeply about what search queries are. This has lead me to consider the idea of topical knowledge as an atomistic concept, an ever-shifting cloud of ideas attached to a central notion. The central notion can be as general […]
Find Out What’s Moving and Shaking With Wikipedia Hot Topics
Wikipedia Hot Topics analyzes the top 1000 Wikipedia pages for a given date, finds the ones which had a significant view bump against a 7-day median (more than 100%), then divides them into categories (living humans, deceased humans, films, even categories like “rare diseases”. The category information is being taken from Wikidata’s P31 “instance of” value.) Each Wikipedia article on the list gets a detail section with more information about the article along with link to external tools and resources.
See How Wikipedia Topics Are Shaking the News With a Wikipedia Seismograph
By visually displaying the deviations from a seven-day moving average in a chart (which looks to me like a seismograph output) you can easily see peaks in the public’s interest in a topic. Of course, that knowledge isn’t very interesting unless you can also discover why the interest has peaked, so the WPS also includes a feature to let you create date-bounded Google News searches using the chart output.
Searching in Data Tide Pools Before Braving Google’s Oceans
I’ve been playing with the idea of building a little wading pool of data that offers a limited but reasonably authoritative collection of information (in this case Wikipedia), and then exploring the relationships between those data to build more complex search engine queries that are less likely to get snared by junk Google results. I made […]
Upgrading WikiCat Main Characters
Last week I wrote about a new tool I made called WikiCat Main Characters. With WMC, you can search for Wikipedia categories by keyword and then explore the people within those categories to find the “main characters” — the people whose Wikipedia articles have had the biggest bump in pageviews over the past month. The […]
Finding the “Main Characters” in Wikipedia Categories
If I gave you a list of twenty people from Wikipedia and told you to list them in order of cultural prominence without consulting an external reference, how would you do it? You’d probably start by identifying people you know. You’d use your knowledge to sort them as best you could. But what about the […]
Shaking Wikipedia Categories to See What Pops Up
I’ve been spending the last few days playing with my favorite mental chew toy, the question “How do you ask for what you don’t know?” It’s an important question because every search engine query above a certain level of complexity involves filling in a knowledge gap. How you understand, define, and contextualize that gap means […]
Making Location-Based Timelines With Wikipedia, Wikidata, and Mojeek
I started learning JavaScript in Mayish 2022. I wanted to make tools to address some of the things I disliked about Google search, and after looking around it seemed like JavaScript was the best solution. So I signed up for a course, thrashed and flailed my way through 50 of the 59 lessons, and then […]
Keep An Eye on the Fediverse With the Mastodon Hashtag Monitor
Over 15 years ago I wrote a book called Information Trapping. It was about how to set up online monitors to find online information around certain keywords and keep it coming as a flow to you via tools like RSS, page monitors, etc. As you might imagine, Information Trapping’s resources and tool listings are very […]
Using ChatGPT to Double-Distill Mojeek Results into a Date-Based Topic Overview
My concern about AI-assisted search results has been, from the beginning, the lack of human context. A simple query is rarely going to be sufficient in itself; after all, the user is searching because of some existing information lack. Outside of the most basic queries (When is a movie playing? Where is that restaurant? How […]