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lib/Lingua/Norms/SUBTLEX.pm  view on Meta::CPAN

L<Statistics::Lite|Statistics::Lite> : for various statistical methods

L<String::Trim|String::Trim> : C<trim>

L<String::Util|String::Util> : for determining valid string values

L<Text::CSV::Hashify|Text::CSV::Hashify> : reads in the specs file

L<Text::CSV::Separator|Text::CSV::Separator> : for determining the field delimiter within the datafiles

L<Text::Unidecode|Text::Unidecode> : for plain ASCII transliterations of Unicode text

=head1 REFERENCES

Brysbaert, M., Buchmeier, M., Conrad, M., Jacobs, A.M., Boelte, J., & Boehl, A. (2011). The word frequency effect: A review of recent developments and implications for the choice of frequency estimates in German. I<Experimental Psychology>, I<58>, 41...

Brysbaert, M., & New, B. (2009). Moving beyond Kucera and Francis: A critical evaluation of current word frequency norms and the introduction of a new and improved word frequency measure for American English. I<Behavior Research Methods>, I<41>, 977-...

Brysbaert, M., New, B., & Keuleers,E. (2012). Adding part-of-speech information to the SUBTLEX-US word frequencies. I<Behavior Research Methods>, I<44>, 991-997. doi: L<10.3758/s13428-012-0190-4|http://dx.doi.org/10.3758/s13428-012-0190-4>

Herdagdelen, A., & Marelli, M. (2017). Social media and language processing: How Facebook and Twitter provide the best frequency estimates for studying word recognition. I<Cognitive Science>, I<41>, 976-995. doi:L<10.1111/cogs.12392|http://dx.doi.org...