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Linguistic Diversity and Social Justice

By Ingrid Piller

Linguistic Diversity and Social Justice "prompts thinking about linguistic disadvantage as a form of structural disadvantage that needs to be recognized and taken seriously."


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Language Evolution: The Windows Approach

By Rudolf Botha

Language Evolution: The Windows Approach addresses the question: "How can we unravel the evolution of language, given that there is no direct evidence about it?"


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Academic Paper


Title: Automated unsupervised authorship analysis using evidence accumulation clustering
Author: Robert Layton
Institution: University of Sheffield
Author: Paul Watters
Homepage: http://www.comp.mq.edu.au/~pwatters
Institution: University of Sheffield
Author: Richard Dazeley
Institution: The University of Ballarat
Linguistic Field: Computational Linguistics; Text/Corpus Linguistics
Abstract: Authorship Analysis aims to extract information about the authorship of documents from features within those documents. Typically, this is performed as a classification task with the aim of identifying the author of a document, given a set of documents of known authorship. Alternatively, unsupervised methods have been developed primarily as visualisation tools to assist the manual discovery of clusters of authorship within a corpus by analysts. However, there is a need in many fields for more sophisticated unsupervised methods to automate the discovery, profiling and organisation of related information through clustering of documents by authorship. An automated and unsupervised methodology for clustering documents by authorship is proposed in this paper. The methodology is named NUANCE, for n-gram Unsupervised Automated Natural Cluster Ensemble. Testing indicates that the derived clusters have a strong correlation to the true authorship of unseen documents.

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This article appears IN Natural Language Engineering Vol. 19, Issue 1, which you can READ on Cambridge's site or on LINGUIST .



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