情感分析-WordNet，sentiWordNet词典 [英] sentiment analysis - wordNet , sentiWordNet lexicon

问题描述

我需要一个正词和负词的列表，并根据其强度和周度为它们分配权重.我有:

I need a list of positive and negative words with the weights assigned to words according to how strong and week they are. I have got :

1.)WordNet-每个单词给出+或-分数.

1.) WordNet - It gives a + or - score for every word.

2.)SentiWordNet-给出[0,1]范围内的正值和负值.

2.) SentiWordNet - Giving positive and negative values in the range [0,1].

我用几句话检查了这些，

I checked these on few words,

爱-wordNet为名词和动词都给出0.0，我不知道为什么我认为它至少在某些方面应该是正的.

love - wordNet is giving 0.0 for both noun and verb, I dont know why i think it should be positive by at least some factor.

压制-WordNet给出-9.93
-SentiWordNet给出-pos和neg均为0.0. (应该为负)

repress - wordNet gives -9.93
- SentiWordNet gives - 0.0 for both pos and neg. (should be negative)

休息-wordNet-2.488
-SentiWordNet-{pos-0.125，neg-0.5}(应该为正)

repose - wordNet - 2.488
- SentiWordNet - { pos - 0.125, neg - 0.5 } (should be positive)

我需要一些帮助来决定使用哪个.

I need some help to decide which one to use.

谢谢.

推荐答案

很多时候，程度和/或极性可能取决于域和/或上下文，因此仅靠单词本身还不足以做出决定.

Quite often the degree and/or polarity may depend on the domain and/or the context, so the word alone isn't really enough to make a decision.

如果您有一些带注释的数据，我建议使用这两种资源提供的分数作为特征，对分类器进行训练.如果不这样做，一种选择是使用与所讨论的域匹配的可用的带有情感注释的语料库之一.我认为，例如，尽管没有任何数据，但整个任务变得有些棘手，尽管在无监督的情感分类方法上有大量工作要做. 无监督的情绪分析

If you have some annotated data, I suggest training a classifier on that using the scores provided by the two resources as features. If you don't, one option is to use one of the available sentiment-annotated corpora that matches the domain in question. Without any data at all the whole task becomes somewhat tricky, although there is a substantial body of work on unsupervised approaches to sentiment classification, I believe, see, e.g. Unsupervised Sentiment Analysis

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