文本分析规则集-自然语言处理 [英] Set of rules for textual analysis - Natural language processing

问题描述

是否存在包含用于文本分析/自然语言处理的规则的指南?

Does there exist a guide with a set of rules for textual analysis / natural language processing?

您是否有一些专门开发的软件包(例如，在Python中)用于文本情感分析?

Do you have some specific developed package (e.g. in Python) for textual sentiment analysis?

这是我遇到的应用程序:

Here is the application I am faced with:

假设我有两个字典，A和B.A包含负"字，B包含正"字.我可以做的是 count 负数和正数.

Let's say I have two dictionaries, A and B. A contains "negative" words, and B contains "positive" words. What I can do is count the negative and the positive number of words.

这产生了一些问题，例如以下内容:假设"exceptionally"是一个positive单词，而"serious"是一个negative单词.

This created some issues, such as the following: let's suppose that "exceptionally" is a positive word, and "serious" is a negative word.

如果我两个单词紧随其后，则我为"exceptionally serious".在这种情况下，这两个词会相互抵消，这意味着我有1个否定词和1个肯定词.这是不正确的，因为实际上这是双重否定.

If I have the two words following each other, I have "exceptionally serious". In such a case, the two words cancel each other, which means I have 1 negative and 1 positive word. This is not true, because in reality it is a double negative.

所以，我的问题是，是否可以应用一套规则来改进代码，或者是否已经考虑了一些软件机制，并应用文本情感分析?在应用了一套规则(例如双重否定)

So, my question is, is there a set of rules I can apply so that I improve my code, or is there some software that already takes into account such mechanisms, and applies textual sentiment analysis? Is there some implementation which I can feed the dictionaries and provide me with textual sentiment after it applies a set of rules such as double negatives?

推荐答案

我们在圣地亚哥州立大学使用nltk和python进行了情感分析.真的很有趣，很容易！以 http://text-processing.com/demo/sentiment/为例，我输入了非常严重"，而且它知道它是NEG.

We did sentiment analysis at San Diego State using nltk with python. Really fun and easy! http://text-processing.com/demo/sentiment/ for an example I entered "exceptionally serious" and it knows that it is NEG.

足够容易遵循的示例: http://www.laurentluce.com/posts/twitter-sentiment-analysis-using-python-and-nltk/

easy enough example to follow: http://www.laurentluce.com/posts/twitter-sentiment-analysis-using-python-and-nltk/

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