Can good writing be differentiated from bad writing through some kind of algorithm? Many have tried to answer this research question. The latest news in this realm comes from Stony Brook University, in which a group of researchers:
…[T]ook 1000 sentences from the beginning of each book. They performed systematic analyses based on lexical and syntactic features that have been proven effective in Natural Language Processing (NLP) tasks such as authorship attribution, genre detection, gender identification, and native language detection.
“To the best of our knowledge, our work is the first that provides quantitative insights into the connection between the writing style and the success of literary works,” Choi says. “Previous work has attempted to gain insights into the ‘secret recipe’ of successful books. But most of these studies were qualitative, based on a dozen books, and focused primarily on high-level content—the personalities of protagonists and antagonists and the plots. Our work examines a considerably larger collection—800 books—over multiple genres, providing insights into lexical, syntactic, and discourse patterns that characterize the writing styles commonly shared among the successful literature.”
I had no idea there was a name for this kind of research. Statistical stylometry is the statistical analysis of variations in literary style between one writer or genre and another. This study reports, for the first time, that the discipline can be effective in distinguishing highly successful literature from its less successful counterpart, achieving accuracy rates as high as 84%.
The best book on writing that I’ve read is Stephen King’s On Writing, in which he echoes the descriptive nature of writing that the researchers back up as well:
[T]he less successful books also rely on verbs that explicitly describe actions and emotions (“wanted”, “took”, “promised”, “cried”, “cheered”), while more successful books favor verbs that describe thought-processing (“recognized”, “remembered”) and verbs that simply serve the purpose of quotes (“say”).