Skip to main content
SimilarExport ZIP
100%

Words from "Eldorado" in order of frequency

✓ Published0🌍 Public
CCliffordAnderson
Last edited Sep 30, 2014
Created on Sep 30, 2014

The visualization ranks words from Poe’s poem “Eldorado” by frequency, showing the most common terms larger and higher in the layout. It uses a force-directed network via `d3.forceSimulation` with link ties between co-occurring words, while font size encodes count. Word positions derive from collision detection and centering forces, not spatial meaning. The data comes from a gist by CliffordAnderson, parsed from the XML list; only the visible frequency values drive the scaling. No additional text or styling is applied beyond the raw SVG text elements.

AI-generated description

Similar vizzes

Loading thumbnail…

<title>Eldorado

The visualization shows a line-by-line reading of Poe’s poem *Eldorado*, mapping each verse’s length and stanza structure as a static typographic grid. It uses D3.js’s `d3.forceSimulation` to arrange the lines into a loose, non-linear cluster, while `d3.select` and `d3.scaleOrdinal` color-code the four stanzas. The poem’s text is drawn from the provided TEI/XML source, with each line rendered as a separate SVG text element. No animation or interaction is present; the layout simply emphasizes the poem’s rhythmic alternation between short and long lines.

CCliffordAnderson
74% match
Loading thumbnail…

Example from Programming4Humanists

This example visualizes word frequency in a text by processing the poem’s lines and filtering out common stopwords. It shows a ranked list of words by their occurrence count, displayed in descending order. The code uses XQuery 3.0 with functions like `fn:tokenize`, `fn:distinct-values`, and `fn:count` to compute frequencies, while reading the source text and stopword list from gist URLs. The rendering approach is a simple textual output of word elements, each carrying a `frequency` attribute, rather than a graphical chart.

CCliffordAnderson
61% match
Loading thumbnail…

Word Cloud

This word cloud visualizes the frequency of words in two classic texts, "The Three Wishes" and "Alice's Adventures in Wonderland," after removing stopwords. The size of each word corresponds to its occurrence count, with colors assigned from a categorical scale. Built with D3.js, it uses the `d3.layout.cloud` API to arrange words and renders them as SVG `<text>` elements. An animation reveals the words over time as the layout algorithm places them.

Aala-wahibi
61% match
Loading thumbnail…

Fork of Word Cloud Example

This word cloud visualization displays physics-related terms and definitions scraped from sources like Wikipedia and dictionaries, with word size encoding frequency. Built with the d3.layout.cloud plugin by Jason Davies, it places words in an 800x300 SVG canvas from a JSON array of text-size pairs, with all words rotated at zero degrees. The code uses d3.scale.linear to map frequency values to grayscale colors, and renders text elements via d3’s SVG selection API.

DDeceptionsInMind
60% match
Loading thumbnail…

<title>"Tie the strings to my life, my Lord"

This visualization uses a force-directed network layout to map Emily Dickinson’s poem “Tie the strings to my life, my Lord” and its textual variants from the TEI-encoded XML source. It shows how alternate word choices and editorial emendations branch from each line, revealing the poem’s structural decisions. The graph is built with `d3.forceSimulation`, where nodes represent individual words or variant readings and links connect sequential lines, with `d3.drag` for interaction. Node size encodes word frequency, and color distinguishes the manuscript (MS) from the 1896 print witness, using `d3.scaleOrdinal`. Hovering triggers `transition.attrTween` to highlight variant paths, while the layout is computed asynchronously from parsed XML via `DOMParser`.

CCliffordAnderson
60% match
Loading thumbnail…

Word Cloud

This word cloud uses D3’s `d3.layout.cloud` to position words by frequency, with font size scaled by each term’s count. The layout runs inside a force simulation, and the rendering draws the words onto an SVG canvas using `d3.select` and `text` elements. The visualization reads a local JSON dataset of words and counts, then animates the cloud’s appearance with a smooth rotation and fade-in transition. Colors are applied from a categorical palette to differentiate word groups, while the overall layout adapts to the container’s size.

SSree Likhith
60% match
Loading thumbnail…

bad words

This visualization presents a force-directed network of profanity-related terms, where each word is a node connected to others based on shared letters or textual relationships. The graph uses `d3.forceSimulation` to position nodes and `d3.forceLink` to draw edges, with node size and color mapping to word frequency or category. The underlying data comes from a text list of explicit terms, parsed into a graph structure in JavaScript. Labels appear on hover, and the layout stabilizes after several ticks, revealing clusters of related slang and sexual terminology.

66ewis
59% match
Loading thumbnail…

Word Cloud Example

This example displays a word cloud of physics-related terms, with font size encoding each word's frequency from the provided dataset. It uses the `d3.layout.cloud` plugin to compute the layout and renders the result as SVG text elements with D3 v3. The cloud rotates words at zero degrees and applies a grayscale color scale based on frequency. An animation gradually places each word into position as the layout algorithm runs.

Kkaviya-ds
59% match