Lexicon-Based Methods for Sentiment Analysis

@article{Taboada2011LexiconBasedMF,
  title={Lexicon-Based Methods for Sentiment Analysis},
  author={Maite Taboada and Julian Brooke and Milan Tofiloski and Kimberly D. Voll and Manfred Stede},
  journal={Computational Linguistics},
  year={2011},
  volume={37},
  pages={267-307}
}
We present a lexicon-based approach to extracting sentiment from text. The Semantic Orientation CALculator (SO-CAL) uses dictionaries of words annotated with their semantic orientation (polarity and strength), and incorporates intensification and negation. SO-CAL is applied to the polarity classification task, the process of assigning a positive or negative label to a text that captures the text's opinion towards its main subject matter. We show that SO-CAL's performance is consistent across… Expand
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References

SHOWING 1-10 OF 146 REFERENCES
Lexicon-based methods for sentiment analysis
TLDR
The Semantic Orientation CALculator (SO-CAL) uses dictionaries of words annotated with their semantic orientation (polarity an... to extract sentiment from text. Expand
Review Sentiment Scoring via a Parse-and-Paraphrase Paradigm
TLDR
An approach to extracting adverb-adjective-noun phrases based on clause structure obtained by parsing sentences into a hierarchical representation is proposed and a robust general solution for modeling the contribution of adverbials and negation to the score for degree of sentiment is proposed. Expand
More than Words: Syntactic Packaging and Implicit Sentiment
TLDR
A strong predictive connection between linguistically well motivated features and implicit sentiment is established, and it is shown how computational approximations of these features can be used to improve on existing state-of-the-art sentiment classification results. Expand
Using appraisal groups for sentiment analysis
TLDR
A new method for sentiment classification based on extracting and analyzing appraisal groups such as ``very good'' or ``not terribly funny'' is presented, based on several task-independent semantic taxonomies based on Appraisal Theory. Expand
Generating High-Coverage Semantic Orientation Lexicons From Overtly Marked Words and a Thesaurus
TLDR
This work proposes a simple approach to generate a high-coverage semantic orientation lexicon, which includes both individual words and multi-word expressions, using only a Roget-like thesaurus and a handful of affixes and has properties that support the Polyanna Hypothesis. Expand
A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts
TLDR
A novel machine-learning method is proposed that applies text-categorization techniques to just the subjective portions of the document, which greatly facilitates incorporation of cross-sentence contextual constraints. Expand
Learning Subjective Adjectives from Corpora
TLDR
This paper identifies strong clues of subjectivity using the results of a method for clustering words according to distributional similarity (Lin 1998), seeded by a small amount of detailed manual annotation. Expand
Mining WordNet for a Fuzzy Sentiment: Sentiment Tag Extraction from WordNet Glosses
TLDR
Net Overlap Score can be used as a measure of the words degree of membership in the fuzzy category of sentiment: the core adjectives were identified most accurately both by STEP and by human annotators, while the words on the periphery of the category had the lowest scores and were associated with low rates of inter-annotator agreement. Expand
What's great and what's not: learning to classify the scope of negation for improved sentiment analysis
TLDR
This paper presents a negation detection system based on a conditional random field modeled using features from an English dependency parser, and a new negation corpus is presented for the domain of English product reviews obtained from the open web. Expand
AVA: Adjective-Verb-Adverb Combinations for Sentiment Analysis
TLDR
The authors propose the AVA (adjective verb adverb) framework for identifying opinions on any given topic using adjectives, adverbs, or verbs for determining the strength of subjective expressions in a sentence or document. Expand
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