Title :
Visualizing text readability
Author :
Karmakar, Saurav ; Zhu, Ying
Author_Institution :
Dept. of Comput. Sci., Georgia State Univ., Atlanta, GA, USA
fDate :
Nov. 30 2010-Dec. 2 2010
Abstract :
Many readability tests have been developed to assess the reading difficulty of a text document. They are largely based on two categories of readability metrics: word complexity and sentence complexity. However, most of the readability tests assign a single readability index for the entire document, making it difficult to assess how the various readability metrics are distributed across the document. We have developed a method for visualizing the text readability metrics that allows readers and writers to quickly identify the distribution of complex words and sentences across a document. Using our visualization, users can quickly compare not only the sentence lengths but also the syntactic structures of sentences. Our readability visualization can help readers and writers to quickly identify complex words, sentences, or paragraphs that are more difficult to read, or quickly compare multiple documents based on their reading complexity.
Keywords :
data visualisation; text analysis; readability metrics; sentence complexity; text document; text readability visualization; word complexity; Color; Complexity theory; Indexes; Motion pictures; Readability metrics; Visualization; Vocabulary; Visualization; complexity depth of field; grammatical structure; readability;
Conference_Titel :
Advanced Information Management and Service (IMS), 2010 6th International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4244-8599-4
Electronic_ISBN :
978-89-88678-32-9