John Blake


John Blake

Online Writing Tool (Use in Google Chrome)

Paste your text into this box. Use the orange buttons to select the type of error to detect or use the yellow buttons to identify various language features. The results will appear in a new tab.

The online writing tool uses regular expressions to search your submitted article for five types of common errors (accuracy, brevity, clarity, objectivity and formality) that were discovered in a corpus of draft research articles in the fields of information and computer science. You can use the language feature detectors to assess how similiar your text is in terms of these feature compared to texts in your target publication.

Brief explanation of error detectors

  • Accuracy errors - use this to find mistakes in grammar and spelling
  • Brevity errors - use this to find verbose terms
  • Clarity errors - use this to find vague or ambiguous terms
  • Objectivity errors - use this to find overly personal or emotive terms
  • Formality errors- use this to find abbreviations, contractions and informal terms

Brief explanation of language feature detectors

  • Modality detector - use this to identity hedges and boosters
  • Voice detector - use this to identify passive voice and the tense used
  • Pronoun detector - use identify the types of pronouns and possessive adjectives used
  • Article detector - use this to identify indefinite articles ("a" and "an") and the definite article ("the")

More detailed information on the detectors is given below:

Accuracy detector

  • Nouns: uncountable nouns - accommodations, clothings, furnitures, homeworks, informations, knowledges, lightnings, luggages, musics, publics, researches, slangs, trainings, transportations, works
  • Nouns: irregular plural nouns +..s, e.g. datas, each data, two data
  • Noun phrases: one of the + plural, each + plural (e.g. each features), a hour, another + plural (e.g. another articles), much + plural (e.g. much helps), many + no plural (e.g. many time)
  • Prepositional phrases: despite followed by clause (e.g. despite there is a problem)
  • Verb phrases: be occurred, be happened, There happened, There occurred, was did, I am belonging
  • Modal verbs: modal verbs followed by -ed, can to
  • Linking: moreover, errant comma before although, Also
  • averagely, more +; this paper concludes that, if
  • Accidentally repeated words (e.g. and and)
  • Collocation - independent mutually, as follow
  • Part of speech errors: (e.g. I analysis, They analysis, I am belong)
  • Careless spelling mistakes (e.g. seve, mesured, randam)

Brevity detector
  • and so on, and so forth, etc, etcetera
  • discuss about
  • day by day, step by step, little by little
  • I think, I do not think

Clarity detector
  • thing, something, you, get, got, researchers say, it is said that,
  • good, bad, excellent, perfect, fabulous, fantastic
  • he, she, they
  • a very long time

Objectivity detector
  • you
  • excellent, perfect, fabulous, fantastic
  • at last, eventually, unfortunately

Formality detector
  • Linking: And, So, But,
  • Contraction using apostrophes, e.g it's,
  • Informal words: lots of, a lot of, really, right after, straight after, right before, straight before, plenty of
  • Wrong character set - Japanese font apostrophe (e.g didn`t)
  • has not been VERB yet
  • Informal phasal verbs: kicked out

Voice detector
  • Regular verbs in passive voice: is, are + am, was + were, has been + have been, will be + going to followed by V-ed
  • Common irregular verbs in passive voice: is, are + am, was + were, has been + have been, will be + going to with the following common past participles:
  • done|said|made|taken|seen|known|given|found|thought|told|become|shown|left|felt|put|brought|begun|kept|held|written|stood|heard|let|meant|set|met|run|paid|sat|spoken|lain|led|read|grown|lost|fallen|sent|built|understood|drawn|broken|spent|cut|risen|driven|bought|worn|chosen)
  • e.g. is done, are said, am made, was taken, were seen, has been known, have been given, will be found, going to be thought

Modality detector
  • Hedges: modal nouns: possibility, likelihood
  • Hedges:modal adverbs: possibly, probably
  • Hedges:modal verbs: may, could, might
  • Hedges:modal adjectives: possible, probable, likely, unlikely
  • Approximations: about, around, approximately, nearly, roughly, more or les
  • Boosters: certainly, certainty, clear, clearly, definitely, manifestly, undoubtedly, always

Pronoun and possessive adjective detector
  • subject pronouns: I, he, she, we, they, You, He, She, We, They, It
  • object pronouns: me, him, her, us, them
  • subject/object pronouns: you, it,
  • reflexive pronouns: myself, yourself, herself, himself, themselves, ourselves, itself
  • personal adjectives: my, your, his, her, their, our, its, My, Your, His, Her, Their, Our, Its

Article detector
  • indefinite articles: a and an
  • definite article: the

Last updated on 23 November 2016.

Related paper

Blake, J. (2012, November 28-30). Corpus-based academic written error detector. Conference proceedings of the 20th International Conference on Computers in Education. Nanyang Technological University, Singapore.

(c) John Blake 2016 with thanks to Maxim Mozgovoy (University of Aizu) for help with JavaScript and Andy Morrall (PolyU) for the initial idea to use regex and adapted script.