We study how Extraversion or Introversion influences people’s language production. A corpus of e-mail texts was gathered from individuals categorised via Eysenck’s EPQ-R personality test. One experiment analysed the corpus using existing content analysis tools, and found relatively weak effects of Extraversion. A second experiment used more sensitive bigram-based techniques from statistical nat...

Advances in computational linguistics and discourse processing have made it possible to automate many language- and text-processing mechanisms. We have developed a computer tool called Coh-Metrix, which analyzes texts on over 200 measures of cohesion, language, and readability. Its modules use lexicons, part-of-speech classifiers, syntactic parsers, templates, corpora, latent semantic analysis,...

The study presented here relies on the integrated use of different kinds of knowledge in order to improve first-guess accuracy in non-word context-sensitive correction for general unrestricted texts. State of the art spelling correction systems, e.g. ispell, apart from detecting spelling errors, also assist the user by offering a set of candidate corrections that are close to the misspelled wor...

As more sensitive data is shared and stored by third-party sites on the Internet, the data in these sites will need to encrypt. The main drawback of encrypting data is that it can be selectively shared only at a coarse-grained level (i.e., giving another party your private key). We progress a new cryptosystem for fine-grained sharing of reencrypted data that we call Key-Policy Attribute-Based E...

This study explores the use of function words for authorship attribution in modern Chinese (C-FWAA). This study consists of three tasks: (1) examine the C-FWAA effectiveness in three genres: novel, essay, and blog; (2) compare the strength of function words as both genre and authorship indicators, and explore the genre interference on C-FWAA; (3) examine whether C-FWAA is sensitive to the time ...