Wikipedia: Sentiment analysis (also known as opinion mining) refers to the use of natural language processing, text analysis and computational linguistics to identify and extract subjective information in source materials.

In 1997, firstly proposed by MIT Professor Rosalind Picard in Effective Computing.

Basic task is classifying the polarity (positive, negative, or neutral). beyond polarity: e.g. emotional states such angry, sad, and happy. Higher: sarcasm?

Application and methodologies:

  • Product, restaurant, or film review rating prediction.

Most statistical classification methods ignore the neutral class.

  • Use a scaling system, give the words an associated number on a -10 to +10 scale.
  • Another direction is subjective/objective identification. Remove objective sentences improve the polarity classification performance.
  • A more fine-grained analysis model is called the feature/aspect-based sentiment analysis.

Chinese Sentiment Dictionary and Resources

Stanford NLP cource on Coursera (Class 7) --> Sentiment Analysis introduced the resources and methods

Query:

Whose sentiment is able to predict the stock movement better? How to find out them?

Sentiment Analysis resources的更多相关文章

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  2. 【Deep Learning Nanodegree Foundation笔记】第 10 课：Sentiment Analysis with Andrew Trask

    In this lesson, Andrew Trask, the author of Grokking Deep Learning, will walk you through using neur ...

  3. 论文阅读：Multi-task Learning for Multi-modal Emotion Recognition and Sentiment Analysis

    论文标题:Multi-task Learning for Multi-modal Emotion Recognition and Sentiment Analysis 论文链接:http://arxi ...

  4. Sentiment analysis in nlp

    Sentiment analysis in nlp The goal of the program is to analysis the article title is Sarcasm or not ...

  5. 使用RNN进行imdb影评情感识别--use RNN to sentiment analysis

    原创帖子,转载请说明出处 一.RNN神经网络结构 RNN隐藏层神经元的连接方式和普通神经网路的连接方式有一个非常明显的区别,就是同一层的神经元的输出也成为了这一层神经元的输入.当然同一时刻的输出是不可 ...

  6. 论文翻译——Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank

    Abstract Semantic word spaces have been very useful but cannot express the meaning of longer phrases ...

  7. Standford CoreNLP--Sentiment Analysis初探

    Stanford CoreNLP功能之一是Sentiment Analysis(情感分析),可以标识出语句的正面或者负面情绪,包括:Positive,Neutral,Negative三个值. 运行有两 ...

  8. 关于情感分类(Sentiment Classification)的文献整理

    最近对NLP中情感分类子方向的研究有些兴趣,在此整理下个人阅读的笔记(持续更新中): 1. Thumbs up? Sentiment classification using machine lear ...

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