Difference between revisions of "The viability of web-derived Polarity Lexicons"
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| − | The authors examine the viability of building large polarity lexicons semi-automatically from the web. They describe a graph propagation approach to build an English lexicon without making use of language dependent resources like Wordnet, POS taggers, etc, as with previous approaches to sentiment analysis. As such the lexicons proposed are not limited to specific word classes and also contain slang, misspellings, multiword expressions, etc. They report a qualitative and quantitative evaluation of the derived lexicons and show superior performances to previously studied lexicons. | + | The authors examine the viability of building large polarity lexicons semi-automatically from the web. They describe a graph propagation approach to build an English lexicon without making use of language dependent resources like Wordnet, POS taggers, etc, as with previous approaches to sentiment analysis. As such the lexicons proposed are not limited to specific word classes and also contain slang, misspellings, multiword expressions, etc. They report a qualitative and quantitative evaluation of the derived lexicons and show superior performances to previously studied lexicons on the sentence polarity classification task. |
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== Dataset Description == | == Dataset Description == | ||
Revision as of 00:28, 2 October 2012
This a Paper reviewed for Social Media Analysis 10-802 in Fall 2012.
Contents
Citation
author = {Leonid Velikovich and
Sasha Blair-Goldensohn and
Kerry Hannan and
Ryan T. McDonald},
title = {The viability of web-derived polarity lexicons},
booktitle = {HLT-NAACL},
year = {2010},
pages = {777-785},
ee = {http://www.aclweb.org/anthology/N10-1119},
bibsource = {DBLP, http://dblp.uni-trier.de}
Online version
The viability of web-derived polarity lexicons
Summary
The authors examine the viability of building large polarity lexicons semi-automatically from the web. They describe a graph propagation approach to build an English lexicon without making use of language dependent resources like Wordnet, POS taggers, etc, as with previous approaches to sentiment analysis. As such the lexicons proposed are not limited to specific word classes and also contain slang, misspellings, multiword expressions, etc. They report a qualitative and quantitative evaluation of the derived lexicons and show superior performances to previously studied lexicons on the sentence polarity classification task.
Dataset Description
Task Description and Evaluation
Polarity lexicons are large lists of phrases that encode the polarity of each phrase either positive or negative often with some score to represent magnitude of polarity.
The authors propose a graph propagation approach inspired by previous work on constructing polarity lexicons from lexical graphs but without using linguistic resources like Wordnet. Instead the graph is built using co-ocurrance statistics from the entire web.
