Python Tutorial: Readability tests

Key Takeaways

in this lesson we will look at a set of interesting features known as readability tests these tests are used to determine the readability of a particular passage in other words it indicates at what educational level a person needs to be in in order to comprehend a particular piece of text the scale usually ranges from primary school up to college graduate level and as in context of the American education system readability tests are done using a mathematical formula that utilizes the word syllable and sentence count of the passage they are routinely used by organizations to determine how easy the publication's are to understand they have also found applications in domains such as fake news and opinion spam detection there are a variety of readability tests in use some of the common ones include the flesh reading ease the gunning fog index the simple measure of gobbledygook are small and the dáil shall scope note that these tests are used for texts in English tests for other languages also exist that take into consideration the nuances of that particular language for the sake of brevity we will cover only the first two scores in detail however once you understand them you will be in a good position to understand and use the other scores to the flush reading ease is one of the oldest and most widely used readability tests the score is based on two ideas the first is that greater the average sentence length harder the text is to read consider of these two sentences the first is easier to follow than the second the second is that the greater the number of a lab average number of syllables in the word the harder the text is to read therefore I live in my home is considered easier to read then I decide in my domicile an account of its usage of lesser syllables per word the higher the Flesch reading ease go the greater is the readability therefore a higher score indicates that the text is easier to understand this table shows how to interpret the Flesch reading ease scores a score above 90 would imply that the text is comprehensible to a fifth grader whereas a score below thirty would imply that the text can only be understood by college graduates the Gunung fog index was developed in 1954 light flesh this code is also dependent on the average sentence length however it uses percentage of complex words in place of average syllables to compute its score here complex words refer to all words that have three or more syllables unlike flesh the formula for gunning fog index is such that the higher the score the more difficult the passage is to understand the index can be interpreted using this table a score of six would indicate sixth grade reading difficulty whereas a score of seventeen would indicate college graduate level reading difficulty we can conduct these readability tests in Python using the text artistic library we import text artistic class from tech statistic next we create a text artistic object and pass in the passage or text we evaluating we then access the dictionary of readability scores from the text artistic object using the scores attribute and then store it in a variable named readability scores finally we access the various scores from the readability scores dictionary using the corresponding skis as shown in this example the text that was passed is between the reading level of a college senior and that of a college graduate let's now practice computing readability scores using the text artistic library