Summary of the paper

Title “He Said She Said” ― a Male/Female Corpus of Polish
Authors Filip Graliński, Łukasz Borchmann and Piotr Wierzchoń
Abstract Gender differences in language use have long been of interest in linguistics. The task of automatic gender attribution has been considered in computational linguistics as well. Most research of this type is done using (usually English) texts with authorship metadata. In this paper, we propose a new method of male/female corpus creation based on gender-specific first-person expressions. The method was applied on CommonCrawl Web corpus for Polish (language, in which gender-revealing first-person expressions are particularly frequent) to yield a large (780M words) and varied collection of men's and women's texts. The whole procedure for building the corpus and filtering out unwanted texts is described in the present paper. The quality check was done on a random sample of the corpus to make sure that the majority (84%) of texts are correctly attributed, natural texts. Some preliminary (socio)linguistic insights (websites and words frequently occurring in male/female fragments) are given as well.
Topics Corpus (Creation, Annotation, etc.), Document Classification, Text categorisation, Person Identification
Full paper “He Said She Said” ― a Male/Female Corpus of Polish
Bibtex @InProceedings{GRALISKI16.905,
  author = {Filip Graliński and Łukasz Borchmann and Piotr Wierzchoń},
  title = {“He Said She Said” ― a Male/Female Corpus of Polish},
  booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)},
  year = {2016},
  month = {may},
  date = {23-28},
  location = {Portoro┼ż, Slovenia},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Sara Goggi and Marko Grobelnik and Bente Maegaard and Joseph Mariani and Helene Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  address = {Paris, France},
  isbn = {978-2-9517408-9-1},
  language = {english}
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