A Word Association Data Processor to Facilitate Robust and Consistent Categorisation and Analysis of Word Associations

A Word Association Data Processor to Facilitate Robust and Consistent Categorisation and Analysis of Word Associations

The Word Association Data Processor (WADP) is an open-source, free software package which automates key aspects of the categorisation and analysis of word association data gathered from respondents in word association tasks. The user base of this software is expected to be linguists and others worki...

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Bibliographic Details
Main Author: Andreas Buerki
Format: Article
Language:English
Published: Ubiquity Press 2025-03-01
Series:Journal of Open Research Software
Subjects:
word association
mental lexicon
psycholinguistics
lexical relations
Online Access:https://account.openresearchsoftware.metajnl.com/index.php/up-j-jors/article/view/399
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Summary:The Word Association Data Processor (WADP) is an open-source, free software package which automates key aspects of the categorisation and analysis of word association data gathered from respondents in word association tasks. The user base of this software is expected to be linguists and others working with word association data and employing a methodology similar to that presented in Fitzpatrick et. al. (2015). The WADP offers three modules. The categoriser module provides an interface for the manual categorisation of word association responses and the automatic categorisation of responses in cases where categorisations for the relevant cue-response pairs are found in a database of past categorisations. It also facilitates the automatic storage of all new ratings in the database and the tracking of respondent IDs (and categoriser/rater IDs if provided) in all input and output files. The reporter module allows the automatic creation of individual response profiles, cue profiles and primary response profiles. Finally, the administrator module performs a number of housekeeping functions such as the merging of two database files (including the resolution of conflicting entries) and producing database files from categorised output data.
ISSN:2049-9647

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