如果您使用 Python，我建议您看一下 NLTK 和 NLTK 书。
此博客：streamhacker.com 有一些非常好的文章可以帮助您入门。
自 2000 年代末以来，该领域已有大量研究。
更新（2013 年 10 月）：
斯坦福大学的研究人员在情感分析方面取得了突破，平均准确率超过 85%。 （http://gigaom.com/2013/10/03/stanford-researchers-to-open-source-model-they-say-has-nailed-sentiment-analysis/）
If you're using Python, I'd suggest you have a look at NLTK and the NLTK book.
This blog: streamhacker.com has some very good articles to get you started.
There's been lots of research in this area in the since the late 2000's.
UPDATE (Oct 2013):
Stanford researches made a breakthrough in sentiment analysis that has achieved more than 85% accuracy on average. (http://gigaom.com/2013/10/03/stanford-researchers-to-open-source-model-they-say-has-nailed-sentiment-analysis/)
在从头开始之前，您可以看一下现有的 NLP 框架。
Before starting from scratch, you can have a look at existing NLP frameworks.
你可以看看WEKA这个软件。它有许多内置的机器学习分类器，可用于情感分类。它要求您将输入数据转换为 ARFF 格式。
You can look at the software WEKA. It has many built-in machine learning classifiers which you can use for sentiment classification.It requires you to convert the input data to ARFF format.
您可以在此处找到一些有趣的数据集，从 NLP、NER 到图像分类、Bounding：https://dataturks.com/projects /趋势
You could find some interesting datasets from NLP, NER to Image Classification, Bounding here: https://dataturks.com/projects/trending
如果您是 nlp 和 python 的初学者，那么您可以尝试一些好的 api 进行情感分析。
以下是一些可用于您的任务的 Api
1.) 情感分析 api
2.) Monkey Learn 情感分析 api
供阅读目的有关情绪分析的重要信息：
If You are a completely beginner for nlp and python , then you can try some good api for sentiment analysis.
Here are some Api that you can use for your task
1.) sentiment analysis api
2.) Monkey Learn api for sentiment analysis
For reading PurposeGreat info on Sentiment Analysis:
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如果您使用 Python，我建议您看一下 NLTK 和 NLTK 书。
此博客：streamhacker.com 有一些非常好的文章可以帮助您入门。
自 2000 年代末以来，该领域已有大量研究。
更新（2013 年 10 月）：
斯坦福大学的研究人员在情感分析方面取得了突破，平均准确率超过 85%。 （http://gigaom.com/2013/10/03/stanford-researchers-to-open-source-model-they-say-has-nailed-sentiment-analysis/）
If you're using Python, I'd suggest you have a look at NLTK and the NLTK book.
This blog: streamhacker.com has some very good articles to get you started.
There's been lots of research in this area in the since the late 2000's.
UPDATE (Oct 2013):
Stanford researches made a breakthrough in sentiment analysis that has achieved more than 85% accuracy on average. (http://gigaom.com/2013/10/03/stanford-researchers-to-open-source-model-they-say-has-nailed-sentiment-analysis/)
在从头开始之前，您可以看一下现有的 NLP 框架。
Before starting from scratch, you can have a look at existing NLP frameworks.
你可以看看WEKA这个软件。它有许多内置的机器学习分类器，可用于情感分类。
它要求您将输入数据转换为 ARFF 格式。
You can look at the software WEKA. It has many built-in machine learning classifiers which you can use for sentiment classification.
It requires you to convert the input data to ARFF format.
您可以在此处找到一些有趣的数据集，从 NLP、NER 到图像分类、Bounding：https://dataturks.com/projects /趋势
You could find some interesting datasets from NLP, NER to Image Classification, Bounding here: https://dataturks.com/projects/trending
如果您是 nlp 和 python 的初学者，那么您可以尝试一些好的 api 进行情感分析。
以下是一些可用于您的任务的 Api
1.) 情感分析 api
2.) Monkey Learn 情感分析 api
供阅读目的
有关情绪分析的重要信息：
If You are a completely beginner for nlp and python , then you can try some good api for sentiment analysis.
Here are some Api that you can use for your task
1.) sentiment analysis api
2.) Monkey Learn api for sentiment analysis
For reading Purpose
Great info on Sentiment Analysis: