There are gender wars, and then there are casualties. It wasn’t until 2011 that the behemoth toymaker LEGO acknowledged girls’ desire to build with bricks, even though the company had long before made a seemingly effortless pivot to co-branding, video games, and major motion pictures. So it’s little wonder that girls face all-too-real obstacles when […]Read more
While a traditional thesaurus can help writers find closely similar words, it rarely helps writers choose the word that means exactly what they are trying to communicate. Nuance matters, and our brainstorming app, Wordakin, is designed to help improve communication. If you want a different word for “jump,” a traditional thesaurus will give you a list of similar words, ranging from little skips to giant bounds. We wanted to develop a tool that could take the words “jump” and “run” and suggest related terms, like “leap” or “rush.”
The result, Wordakin, is part reference app and part adventure. Users plant two seed words, and the app uses these to produce a bounty of words that connect the two. A next-generation thesaurus, Wordakin goes beyond synonyms to deliver close and distant word associations. As such, it helps users find the words on the tips of their tongues and furnishes an abundance of choices that convey precise meaning.
Built on IDEA’s Linguabase, Wordakin users can choose among more than half a million words and tap into the app’s built-in dictionary. Word buffs can enjoy stitching together more disparate words (e.g., “light” and “dark”), which are often connectable since many words have more than one meaning or sense. For fun, the app can display random pairs of seed words.
Technically, the app returns one- to two-dozen connections from a massive network, called a “graph,” of connected words. We have calculated the relatedness of all English words and use a variation of the Dijkstra algorithm to find words with the least degrees of separation.
Exploring these relations can be a fascinating view into pools of words that have related meanings or are commonly used in a similar context.
Coming late 2016.