Finding Opinionated Blogs Using Statistical Classifiers and Lexical Features
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Summary
This paper systematically exploited various lexical features for opinion analysis on blog data using a statistical learning framework and achieves reasonable performance, but does not rely on much human knowledge or deep level linguistic analysis.
- Type
- article
- Published
- 2009-03-20
- Cited by
- 14
- References
- 11
- Access
- Open access
- OpenAlex
- https://openalex.org/W77857456
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:7110151
Keywords
Computer science, Artificial intelligence, Sentiment analysis, Task (project management), Natural language processing
References
- Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews
- Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis
- Automatic Identification of Sentiment Vocabulary: Exploiting Low Association with Known Sentiment Terms
- Learning Extraction Patterns for Subjective Expressions
- Multi-domain Sentiment Classification
- Mining the peanut gallery: opinion extraction and semantic classification of product reviews
- Mining and summarizing customer reviews
- Thumbs up? Sentiment Classification using Machine Learning Techniques
- Predicting the Semantic Orientation of Adjectives
- Sentiment Analysis: Adjectives and Adverbs are Better than Adjectives Alone
- Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews
- Overview of the TREC 2008 Blog Track
Cited by
- Identifying and isolating text classification signals from domain and genre noise for sentiment analysis
- A Study of Dependency Features for Chinese Sentiment Classification
- Information Retrieval on the Blogosphere
- Evaluation in Discourse: a Corpus-Based Study
- Sentiment Analysis and Opinion Mining
- Big Data Analysis for Personalized Health Activities: Machine Learning Processing for Automatic Keyword Extraction Approach
- Sentence Subjectivity and Sentiment Classification
- Opinion Mining on the Web 2.0 - Characteristics of User Generated Content and Their Impacts
- Sentiment Analysis: Aspect and Entity Extraction
- Document Sentiment Classification
- The Problem of Sentiment Analysis
- Analysis of Comparative Opinions
- Opinion Summarization and Search
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