Explore the CHI 2024 papers using sentence-embeddings. Enter a query in and see the most relevant papers according to their title and abstract. In the scatterplot two papers should be closer together if they have similar contents. You can also drag on the chart to filter. The system works by computing sentence embeddings on the papers text, then applying dimensionality reduction on the embeddings to compute the scatterplot. You can even change the dimensionality reduction and embeddings algorithm and parameters. h/t https://www.downes.ca/post/76576
If you want to make a really big AI model — the kind that can generate images or do your homework, or build this website, or fake a moon landing — you start by finding a really big training set. brilliant visualization
The Best WordPress Table & Chart Plugin - wpDataTables
wpDataTables is a best-selling WordPress table plugin which makes your work with tables, charts and data management easy. 70,000+ companies and individuals already trust wpDataTables to work with financial, scientific, statistical, commercial and other data.
The Global River Runner is a vizualization simulating the path a raindrop would take, assuming it runs off into a stream and from then on to a terminating location, likely an inland water body or the ocean. A running list of interesting flow paths can be found here. The Global River Runner is an open source Work In Progress, based on open data and open source software components, some of which themselves are in early or alpha development stages (all described in detail below). The vast majority of river paths calculated are based on topographic data collected and processed automatically, and may not reflect true river paths that may be affected by engineered features such as dams, canals, and conduits. The front end visualization was developed by Sam Learner. The back end is developed by Dave Blodgett, Kyle Onda and Ben Webb as a demonstrator of several key aspects of the Internet of Water project, including leveraging open data, open source software, and open standards to create innovative water information products and applications.
Gets Mastodon statuses data based on a defined hashtag and provides a clean HTML file with tables and graphs (who authored, who most replied to others, other hashtags, who was replied to).
In graphics: a world of languages - and how many speak them | South China Morning Post
There are at least 7,102 known languages alive in the world today. Twenty-three of these languages are a mother tongue for more than 50 million people. The 23 languages make up the native tongue of 4.1 billion people. We represent each language within black borders and then provide the numbers of native speakers (in millions) by country. The colour of these countries shows how languages have taken root in many different regions Click to view the full-size infographic in high resolution.
SQID is a fast way to browse and query Wikidata, the free knowledge base of Wikipedia. SQID is inspired by Magnus Manske's Reasonator, but it has a different focus. In particular, information about Wikidata classes and properties is prominently shown, including derived statistics and query results that are not part of Wikidata. SQID wants to help editors to improve Wikidata.
Chartability is a methodology for ensuring that data visualizations, systems, and interfaces are accessible. Chartability is organized into principles with testable criteria and focused on creating an outcome that is an inclusive data experience for people with disabilities.
When you’re working with large amounts of data in a Google Sheets spreadsheet, it isn’t always convenient to drop a chart into the mix. To help you, you can create one-cell charts using the SPARKLINE function instead. A sparkline chart is a very small line chart that allows you to quickly visualize your data. It’s useful if you want to quickly see if share price data in a spreadsheet was going up or down, for instance. The SPARKLINE function in Google Sheets allows you to insert these types of charts into a single cell on your spreadsheet. While a sparkline is typically a line chart, the SPARKLINE function enables you to create alternatives, including single-cell bar and column charts.
Canadian Climate Opinion Maps 2018 - Yale Program on Climate Change Communication
Public opinion on climate change is an important input into the decision-making process for the development of policies to reduce climate change impacts or prepare for these impacts. Yet opinions can vary widely depending on where people live. So why rely on just a single national average to understand public responses to climate change at the provincial and local levels? Public opinion polling is generally done at the national level because local level polling is very costly and time consuming. Our team, however, has developed a geographic and statistical model to downscale national public opinion results to the province and riding level. We can now estimate and visualize differences in opinion across the country, allowing a clearer picture of the diversity of Canadian perceptions, attitudes, and support for policy to come into focus. For instance, we estimate that nationally, 83% of Canadians perceive that climate change is happening. Meanwhile, only 60% in the Souris–Moose Mountain riding in Saskatchewan share this view, compared to 93% in the riding of Halifax. Explore the maps by clicking on your province or riding and compare the results across questions and geographic areas. Beneath each map are bar charts displaying the results for every question at whichever geographic scale is currently selected. See the FAQ tab (above) for more information about error estimates.
The mind-mapping.org Blog – This blog is about software for visual thinking and organising information. It will give you the low-down on developments in the world of visual networks and all types of business maps.
This blog is about software for visual thinking and organising information. It will give you the low-down on developments in the world of visual networks and all types of business maps.
How to prepare your data for analysis and charting in Excel & Google Sheets | Chartable
This article tries to explain the methods and Excel formulas you’ll need most often to get your data ready to analyze or plug into Datawrapper. Note that tidying up your data as described here is not the same as making your numbers as readable or as beautiful-looking as possible. That will come later. We need to make our data readable for software like Excel or Datawrapper before we can bother making it readable for humans.
visualizing memes : culturegraphy - culture - memes - visualization
Culturegraphy investigates cultural information exchange over time also known as 'memes'. These networks can provide new insights into the rich interconnections of cultural development. Treating cultural works as nodes and influences as directed edges, the visualization of these cultural networks can provide new insights into the rich interconnections of cultural development. The graphics represent complex relationships of movie references by combining macro views summarizing 100 years of movie influences with micro views providing a close-up look at the embedding of individual movies. The macro view shows the rise of the self-referential character of postmodern cinema, while the micro level illustrates differences between individual movies, when they were referenced and by whom. The visualizations provide views that are closer to the real complexity of the relationships than aggregated views or rankings could do.
USAFacts is a new data-driven portrait of the American population, our government’s finances, and government’s impact on society. We are a non-partisan, not-for-profit civic initiative and have no political agenda or commercial motive. We provide this information as a free public service and are committed to maintaining and expanding it in the future. We rely exclusively on publicly available government data sources. We don’t make judgments or prescribe specific policies. Whether government money is spent wisely or not, whether our quality of life is improving or getting worse – that’s for you to decide. We hope to spur serious, reasoned, and informed debate on the purpose and functions of government. Such debate is vital to our democracy. We hope that USAFacts will make a modest contribution toward building consensus and finding solutions. There’s more to USAFacts than this website. We also offer an annual report, a summary report, and a “10-K” modeled on the document public companies submit annually to the SEC for transparency and accountability to their investors.
Tweets are visualized in different ways in each of the tabs at the top of the window. Sentiment. Each tweet is shown as a circle positioned by sentiment, an estimate of the emotion contained in the tweet's text. Unpleasant tweets are drawn as blue circles on the left, and pleasant tweets as green circles on the right. Sedate tweets are drawn as darker circles on the bottom, and active tweets as brighter circles on the top. Hover your mouse over a tweet or click on it to see its text. Topics. Tweets about a common topic are grouped into topic clusters. Keywords above a cluster indicate its topic. Tweets that do not belong to a topic are visualized as singletons on the right. Hover your mouse over a tweet or click on it to see its text. Heatmap. Pleasure and arousal are used to divide sentiment into a 8×8 grid. The number of tweets that lie within each grid cell are counted and used to color the cell: red for more tweets than average, and blue for fewer tweets than average. White cells contain no tweets. Hover your mouse over a cell to see its tweet count. Tag Cloud. Common words from the emotional regions Upset, Happy, Relaxed, and Unhappy are shown. Words that are more frequent are larger. Hover the mouse over a word to see how often it occurred. Timeline. Tweets are drawn in a bar chart to show the number of tweets posted at different times. Pleasant tweets are shown in green on the top of the chart, and unpleasant tweets are shown in blue on the bottom. Hover the mouse over a bar to see how many tweets were posted at the given time. Map. Tweets are drawn on a map of the world at the location where they were posted. Please note most Twitter users do not provide their location, so only a few tweets will be shown on the map. Hover your mouse over a tweet or click on it to see its text. Affinity. Frequent tweets, people, hashtags, and URLs are drawn in a graph to show important actors in the tweet set, and any relationship or affinity they have to one another. Hover your mouse over a node, or click on a node to see its tweets. Tweets. Tweets are listed to show their date, author, pleasure, arousal, and text. You can click on a column's header to sort by that column.
What If Your Computer Could See Like You? (Intel IQ magazine)
RealSense showed us that we can build personal devices that begin to have human sensibilities. Once our computers can perceive depth, shift their focus and read human emotions or gestures, it opens up new possibilities for our devices to become even more helpful in our lives. “We kept asking ourselves: What would be different if your computer could see like a person?” We’ve captured some of this fascination in a special edition of iQ we’re calling Science of Seeing, where you can learn how RealSense went from idea to reality. You can also explore how the technology works and how you might use it in your life. Along the way, you just might gain a deeper appreciation for the power of seeing.
"In the framework of our researches, we are focusing on twitter visualization. This social platform indeed offers several opportunities for data visualization: social ties analysis, links between geography and themes/languages, real-time visualization of a particular topic (like a conference), or again to analyse a past topic and its “storyfication”. "
Mapbox Studio, our open source map design platform, launches today across all platforms; Mac OS X, Windows and Linux. Studio allows anyone to design radically custom maps, easily work with huge global datasets, publish updates in seconds, and design with resolution independence from retina devices to high resolution printing. It's the first map design application built from the ground up using vector tiles, providing a new level of design control and interaction, all while being more performant - lighter and faster on any mobile app and web site. Now you can style maps faster, your data simply scales, and everything renders sharper than ever before.
"This website is designed to help you understand some basic git concepts visually. This is my first attempt at using both SVG and D3. I hope it is helpful to you. Adding/staging your files for commit will not be covered by this site. In all sandbox playgrounds on this site, just pretend that you always have files staged and ready to commit at all times. If you need a refresher on how to add or stage files for commit, please read Git Basics. "
This empirical project attempts to provide a transformative and novel answer to a foundational issue for science, technology, engineering and mathematics (STEM) learning: How can we measure the development of complex STEM thinking? Young people today need to develop complex thinking in STEM in order to participate in the social, economic, and cultural life of a globalized world. Yet we cannot create curricula, programs, or activities to teach complex STEM thinking unless we can measure and show whether students have developed it. In this project, we propose to develop epistemic network analysis (ENA) as a toolkit for measuring complex STEM thinking. Our goal is to develop tools and techniques that will be applicable to any form of complex STEM thinking, and thus our research and dissemination plan is explicitly designed to extend ENA to other STEM domains. This project is based on the psychological theory of epistemic frames, which suggests that complex thinking in any field requir
Embedly Blog, Visualizing discussions on Reddit with a D3 network and Embedly
Recently, we had an Embedly hack week where internally we played with ideas to make something cool. I made a Reddit discussion network visualization, powered by D3 with previews generated by Embedly jQuery, and UI by Foundation.
A visualization of your reddit comment history. Graph daily, weekly, and long term usage patterns, find old posts that have been buried, and view top comments.
Netlytic is a cloud-based text and social networks analyzer that can automatically summarize large volumes of text and discover social networks from online conversations on social media sites such as Twitter, Youtube, blogs, online forums and chats.
