{"id":837,"date":"2015-07-16T10:00:06","date_gmt":"2015-07-16T10:00:06","guid":{"rendered":"http:\/\/localhost\/?p=837"},"modified":"2018-04-30T16:15:57","modified_gmt":"2018-04-30T15:15:57","slug":"displaying-data-analysing-text","status":"publish","type":"post","link":"https:\/\/visualagency.com\/?p=837","title":{"rendered":"Displaying Data: Analysing Text"},"content":{"rendered":"

Language is our primary form of communication, as the words we write or speak are used as tools to transfer meaning. \u00a0But what meaning can data visualisation give about words? \u00a0Can data visualisation reveal patterns and insights into large bodies of text or is it used simply as a medium to produce art?<\/p>\n

In this post for our ongoing series on Displaying Data, I’ll be looking at ways bodies of text have been visualised.<\/p>\n

Word Clouds<\/h2>\n

Also known as a “Tag Cloud”, this form of visualising text displays how frequently words appear in a body of text, by displaying a cluster of words in which\u00a0they are all\u00a0sized in proportion to their frequency. \u00a0You can see an example of this below, where I’ve used the text Plato’s Republic as an example:<\/p>\n

\"analysing<\/p>\n

You can see words like “Yes”, “one” and “good” stand out the most, which shows that these words have been used and repeated the most in the book.<\/p>\n

While this is the typical format for Word Clouds, they’re not limited to clusters\/clouds. \u00a0The words can also be arranged in layouts other than a cloud cluster: on horizontal lines, columns or within a shape. Also, the size of the words can be in proportion to another variable assigned to them, not\u00a0just by their frequency. \u00a0A good example of this would be to display a Word Cloud with all the World’s countries and have the size of the country’s name in proportion to its population size or GDP.<\/p>\n

The downside to Word Clouds are that longer words and words that contain many ascenders and descenders are given more emphasis. \u00a0Also World Clouds are not great for any analytical accuracy and are therefore more for aesthetic use.<\/p>\n

Word Clouds are not so popular anymore, as they have a bad reputation of being tacky and cheesy. However, below are some great examples of where Word Clouds have been combined with other methods of displaying data visualisation to produce some interesting results.<\/p>\n

US presidential inauguration speeches: how does Obama’s second compare?<\/h2>\n

Working for The Guardian, Santiago Ortiz created\u00a0a visualisation that\u00a0uses all the words said in every US Presidential inauguration speech since Richard Nixon in 1969.<\/p>\n

\"analysing<\/a>
Source: The Guardian<\/a><\/figcaption><\/figure>\n

The colours used are assigned to each\u00a0US President, which you can see in the legend at the bottom. Ortiz has\u00a0combined both a Word Cloud and a 100% Bar Graph to produce this visualisation: the size\u00a0of each word in all speeches are displayed in proportion to their frequency, while a 100% Bar Graph is displayed behind each word and is segmented based on how much each President has said it.<\/p>\n

Filters are also in place\u00a0to narrow down results. \u00a0Hovering your mouse over a word will only show the other words connected to it and the frequency it’s been mentioned by each President is displayed in the legend at the bottom as a mini bar graph. \u00a0If you hover the mouse over each President in the legend, then only their Word Clouds are displayed.<\/p>\n

The Republican Nation Convention<\/h2>\n

Another political visualisation here from The New York Times, which has visualised how frequently speakers at the Republican Nation Convention have used specific phrases and words. \u00a0The data are sourced from the Federal News Service and is continuously updated.<\/p>\n

\"analysing<\/a>
Source: The New York Times<\/a><\/figcaption><\/figure>\n

This visualisation has combined\u00a0a Word Cloud with a proportional area chart (displaying shapes in proportion to the data amount) and has displayed the number of mentions, allowing to accurate referencing. \u00a0Clicking on a “word bubble” will highlight every mention of that word in the transcripts below.<\/p>\n

Word Trees<\/h2>\n

In this visualisation method, a tree of phrases is depicts the parallel sequencing of words in a body of text. \u00a0Like a Word Cloud, the size of the words displayed is proportional to their usage. \u00a0Word Trees are useful for showing which words most follow or precede a target word or to show a hierarchy of the terms.<\/p>\n

\"analysing<\/a>
Source: The Wordtree<\/a><\/figcaption><\/figure>\n

Understanding Shakespeare<\/h2>\n

In this B.A. thesis project, Stephan Thiel introduced a new way of reading drama to help people understand Shakespeare’s work. \u00a0Thiel produced an interesting variety of new ways in which we consume written narrative work and knowledge through the use of code and data visualisation.<\/p>\n

\"analysing<\/a>
Source: Understanding Shakespeare<\/a><\/figcaption><\/figure>\n

In the above example, the major character’s speeches have been highlighted yellow to illustrate the amount of spoke words they’ve used, compared to the rest of the play. Also the size of each word is displayed in proportion to its frequency.<\/p>\n","protected":false},"excerpt":{"rendered":"

Language is our primary form of communication, as the words we write or speak are used as tools to transfer meaning. \u00a0But what meaning can data visualisation give about words? \u00a0Can data visualisation reveal patterns and insights into large bodies of text or is it used simply as a medium to produce art? In this … Read more<\/a><\/p>\n","protected":false},"author":5,"featured_media":4132,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_mi_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"generate_page_header":"","footnotes":""},"categories":[14],"tags":[81,8,75,91,92,93],"acf":[],"yoast_head":"\nDisplaying Data: Analysing Text - VISU.AL AGENCY<\/title>\n<meta name=\"description\" content=\"In this post in our ongoing series of displaying data we'll be looking at analysing text with data visualisation.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/visualagency.com\/?p=837\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Displaying Data: Analysing Text - 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