4月 30

# Sentiment & Opinion 语料记录和整理

sentiwordnet，一直记得有这么个玩意，看是忘记它名字了，找的我好苦啊

http://home.autos.msn.com/ 这个是Car Domain的！好地方。

4月 23

# opinion 有用的素材

1.Identifying Noun Product Features that Imply Opinions

Identifying Noun Product Features that Imply Opinions里面用的是Lexicon-Based Approach to Opinion Mining

Bing Liu 的 Sentiment Analysis and Opinion Mining可以在写related work的时候拿来抄抄

9月 25

# EMNLP09-12 Sentiment 枚举

Review Sentiment Scoring via a Parse-and-Paraphrase Paradigm

Adapting a Polarity Lexicon using Integer Linear Programming for Domain-Specific Sentiment Classification
Integer Linear Programming 整数线性规划，连续看了两篇文章，虽然不懂，但是记一下。

Using Morphological and Syntactic Structures for Chinese Opinion Analysis

Phrase Dependency Parsing for Opinion Mining

———————————- 神奇的分割线，以下EMNLP 2010 ———————————-

Multi-level Structured Models for Document-level Sentiment Classification

———————————- 神奇的分割线，以下EMNLP 2011 ———————————-

Domain-Assisted Product Aspect Hierarchy Generation: Towards Hierarchical Organization of Unstructured Consumer Reviews

Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions

2013@3@22 我改变看法了，在Deep Learning大行其道的今天，应该了解这个~

Unsupervised Discovery of Discourse Relations for Eliminating Intra-sentence Polarity Ambiguities

Structural Opinion Mining for Graph-based Sentiment Representation

9月 14

# ACL09-12 Sentiment 枚举

———————————- 神奇的分割线，以下ACL2007———————————-

PageRankingWordNet Synsets: An Application to Opinion Mining

Structured Models for Fine-to-Coarse Sentiment Analysis

———————————- 神奇的分割线，以下ACL2009 ———————————-

Co-Training for Cross-Lingual Sentiment Classification

A Non-negative Matrix Tri-factorization Approach to Sentiment Classification with Lexical Prior Knowledge

Mine the Easy, Classify the Hard: A Semi-Supervised Approach to Automatic Sentiment Classification

Answering Opinion Questions with Random Walks on Graphs

———————————- 神奇的分割线，以下ACL2010 ———————————-

Identifying Text Polarity Using RandomWalks

Sentiment Learning on Product Reviews via Sentiment Ontology Tree

Employing Personal/Impersonal Views in Supervised and Semi-supervised Sentiment Classification

Generating Focused Topic-specific Sentiment Lexicons

A study of Information Retrieval weighting schemes for sentiment analysis

———————————- 神奇的分割线，以下ACL2011 ———————————-

Automatically Extracting Polarity-Bearing Topics for Cross-Domain Sentiment Classification

Using Multiple Sources to Construct a Sentiment Sensitive Thesaurus for Cross-Domain Sentiment Classification

Learning Word Vectors for Sentiment Analysis