- Eika_Evelyn_1441.pdf (532k)
Readability of text on the web is a key prerequisite for achieving universal accessibility. The World Wide Web Consortium’s Web Content Accessibility Guidelines state that general text should not require reading levels more advanced than lower secondary education. The subsequent research into readability on the web is limited. However, the literature on measuring readability and reading level is vast, but limited to simple measures of sentence length and word difficulty. This study explores the value of using other features that are harder to acquire manually, but are now readily available through computer technology. Our results indicate that the proposed features are not as accurate predictors to readability as the classic measurements. There may thus be some way to go before we have reliable automatic means of assessing texts on the web for readability.
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