Quantifying literature quality using complexity criteria
This work addresses the problem of automated text quality assessment for literature analysis, though it appears incremental as it builds on existing readability indices.
The researchers tackled the problem of quantifying literature quality by measuring entropy and symbolic diversity in English and Spanish texts from Nobel laureates and other authors, finding correlations between these metrics and writing quality, with results suggesting the plausibility of automated quality assessment.
We measured entropy and symbolic diversity for English and Spanish texts including literature Nobel laureates and other famous authors. Entropy, symbol diversity and symbol frequency profiles were compared for these four groups. We also built a scale sensitive to the quality of writing and evaluated its relationship with the Flesch's readability index for English and the Szigriszt's perspicuity index for Spanish. Results suggest a correlation between entropy and word diversity with quality of writing. Text genre also influences the resulting entropy and diversity of the text. Results suggest the plausibility of automated quality assessment of texts.