Describing Words
Here are some adjectives for superficiality. You can get the definitions of these adjectives by clicking on them. You might also like some words related to superficiality (and find more here).
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Click words for definitions.
Words to Describe superficiality
Below is a list of describing words for superficiality. You can sort the descriptive words by uniqueness or commonness using the button above. Sorry if there's a few unusual suggestions! The algorithm isn't perfect, but it does a pretty good job for most common nouns. Here's the list of words that can be used to describe superficiality:
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Words to Describe superficiality
As you've probably noticed, adjectives for "superficiality" are listed above. According to the algorithm that drives this website, the top 5 adjectives for "superficiality" are: complacent, polite, doped and simple-minded, shallow, brilliant, timid and scrupulous, and damned sentimental. There are 92 other words to describe superficiality listed above. Hopefully the above generated list of words to describe superficiality suits your needs.
If you're getting strange results, it may be that your query isn't quite in the right format. The search box should be a simple word or phrase, like "tiger" or "blue eyes". A search for words to describe "people who have blue eyes" will likely return zero results. So if you're not getting ideal results, check that your search term, "superficiality" isn't confusing the engine in this manner.
Note also that if there aren't many superficiality adjectives, or if there are none at all, it could be that your search term has an abiguous part-of-speech. For example, the word "blue" can be an noun and an adjective. This confuses the engine and so you might not get many adjectives describing it. I may look into fixing this in the future. You might also be wondering: What type of word is superficiality?
Describing Words
The idea for the Describing Words engine came when I was building the engine for Related Words (it's like a thesaurus, but gives you a much broader set of related words, rather than just synonyms). While playing around with word vectors and the "HasProperty" API of conceptnet, I had a bit of fun trying to get the adjectives which commonly describe a word. Eventually I realised that there's a much better way of doing this: parse books!
Project Gutenberg was the initial corpus, but the parser got greedier and greedier and I ended up feeding it somewhere around 100 gigabytes of text files - mostly fiction, including many contemporary works. The parser simply looks through each book and pulls out the various descriptions of nouns.
Hopefully it's more than just a novelty and some people will actually find it useful for their writing and brainstorming, but one neat little thing to try is to compare two nouns which are similar, but different in some significant way - for example, gender is interesting: "woman" versus "man" and "boy" versus "girl". On an inital quick analysis it seems that authors of fiction are at least 4x more likely to describe women (as opposed to men) with beauty-related terms (regarding their weight, features and general attractiveness). In fact, "beautiful" is possibly the most widely used adjective for women in all of the world's literature, which is quite in line with the general unidimensional representation of women in many other media forms. If anyone wants to do further research into this, let me know and I can give you a lot more data (for example, there are about 25000 different entries for "woman" - too many to show here).
The blueness of the results represents their relative frequency. You can hover over an item for a second and the frequency score should pop up. The "uniqueness" sorting is default, and thanks to my Complicated Algorithm™, it orders them by the adjectives' uniqueness to that particular noun relative to other nouns (it's actually pretty simple). As you'd expect, you can click the "Sort By Usage Frequency" button to adjectives by their usage frequency for that noun.
Special thanks to the contributors of the open-source mongodb which was used in this project.
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