Identification of effective predictive variables for document qualities

✍ Scribed by Kwong Bor Ng; Rong Tang; Sharon Small; Tomek Strzalkowski; Paul Kantor; Robert Rittman; Peng Song; Ying Sun; Nina Wacholder

• Publisher: Wiley (John Wiley & Sons)
• Year: 2005
• Tongue: English
• Weight: 742 KB
• Volume: 40
• Category: Article
• ISSN: 0044-7870
• DOI: 10.1002/meet.1450400128

✦ Synopsis

Abstract

We analyzed textual properties of documents to identify predictive variables for various document qualities by means of statistical and linguistic methods. We have created a collection of 1000 documents, each document has been judged in terms of nine document qualities (accuracy, reliability, objectivity, depth, author/producer credibility, readability, verbosity and conciseness, grammatical correctness, one‐sided or multiview.) Employing statistical analyses, we considered a kind of linear combination, asking (1) if it was possible to combine textual features linearly to predict document qualities; (2) what textual features had good predictive power; (3) what textual features were minimally required for prediction with a detection rate much better than the false alarm rate. We present several promising results, indicating that with a few number of textual features, we can predict various document qualities much better than chance.