Publishing Partner: Cambridge University Press CUP Extra Wiley-Blackwell Publisher Login
amazon logo
More Info


New from Oxford University Press!

ad

The Vulgar Tongue: Green's History of Slang

By Jonathon Green

A comprehensive history of slang in the English speaking world by its leading lexicographer.


New from Cambridge University Press!

ad

The Universal Structure of Categories: Towards a Formal Typology

By Martina Wiltschko

This book presents a new theory of grammatical categories - the Universal Spine Hypothesis - and reinforces generative notions of Universal Grammar while accommodating insights from linguistic typology.


New from Brill!

ad

Brill's MyBook Program

Do you have access to Dynamics of Morphological Productivity through your library? Then you can by the paperback for only €25 or $25! Find out more about Brill's MyBook program!


Academic Paper


Title: Unsupervised lexicon induction for clause-level detection of evaluations
Author: Hiroshi Kanayama
Institution: IBM Research – Tokyo
Author: Tetsuya Nasukawa
Institution: IBM Research – Tokyo
Linguistic Field: Computational Linguistics; Text/Corpus Linguistics
Abstract: This article proposes clause-level evaluation detection, which is a fine-grained type of opinion mining, and describes an unsupervised lexicon building method for capturing domain-specific knowledge by leveraging the similar polarities of sentiments between adjacent clauses. The lexical entries to be acquired are called polar atoms, the minimum human-understandable syntactic structures that specify the polarity of clauses. As a hint to obtain candidate polar atoms, we use context coherency, the tendency for the same polarity to appear successively in a context. Using the overall density and precision of coherency in the corpus, the statistical estimation picks up appropriate polar atoms from among the candidates, without any manual tuning of the threshold values. The experimental results show that the precision of polarity assignment with the automatically acquired lexicon was 83 per cent on average, and our method is robust for corpora in diverse domains and for the size of the initial lexicon.

CUP at LINGUIST

This article appears in Natural Language Engineering Vol. 18, Issue 1, which you can read on Cambridge's site .



Back
Add a new paper
Return to Academic Papers main page
Return to Directory of Linguists main page