如何为一个句子计算极性? (在情绪分析中) [英] How is polarity calculated for a sentence ??? (in sentiment analysis)

问题描述

如何计算语句中单词的极性....就像

How is polarity of words in a statement are calculated....like

我成功地完成了任务，但徒劳无功"

"i am successful in accomplishing the task,but in vain"

每个单词如何评分? (例如-成功-0.7完成-0.8但--0.5 徒劳的--0.8) 如何计算?每个单词如何得到一个值或分数?发生了什么事?在进行情感分析时，我几乎没有什么要弄清楚的.如果有人事先提供帮助，那就太好了

how each word is scored? (like - successful- 0.7 accomplishing- 0.8 but - -0.5 vain - - 0.8) how is it calculated ? how is each word given a value or score?? what is the thing that's going behind ? As i am doing sentiment analysis I have few thing to be clear so .that would be great if someone helps.thanks in advance

推荐答案

单个单词的分数可以来自预定义的单词列表，例如ANEW，一般询问者，SentiWordNet，LabMT或我的AFINN.要么是专家给他们打分，要么是学生打分，或者是Amazon Mechanical Turk工人打分.显然，这些分数并不是最终的真理.

The scores from individual words can come from predefined word lists such as ANEW, General Inquirer, SentiWordNet, LabMT or my AFINN. Either individual experts have scored them or students or Amazon Mechanical Turk workers. Obviously, these scores are not the ultimate truth.

单词分数也可以通过带注释文本的监督学习来计算，或者可以从单词本体或共现模式中估算出来.

Word scores can also be computed by supervised learning with annotated texts, or word scores can be estimated from word ontologies or co-occurence patterns.

关于单个单词的聚合，有多种方法.一种方法是将所有单个分数(价)相加，另一种方法是将单词中的最大价相加，第三种方法是将单词数或计分的单词数归一化(除以)(即获得平均分数) )--或除以该数字的平方根.结果可能有所不同. 我对我的AFINN单词列表进行了一些评估: http ://www2.imm.dtu.dk/pubdb/views/edoc_download.php/6028/pdf/imm6028.pdf

As for aggregation of individual words, there are various ways. One way would be to sum all the individual scores (valences), another to take the max valence among the words, a third to normalize (divide) by the number of words or by the number of scored words (i.e., getting a mean score), - or divide the square root of that number. The results may differ a bit. I made some evaluation with my AFINN word list: http://www2.imm.dtu.dk/pubdb/views/edoc_download.php/6028/pdf/imm6028.pdf

另一种方法是使用像Richard Socher的模型这样的递归模型.各个单词的情感价值以树状结构汇总，应该发现示例中的但无济于事"部分应具有最大的分量.

Another approach is with recursive models like Richard Socher's models. The sentiment values of the individual words are aggregated in a tree-like structure and should find that the "but in vain"-part of your example should carry the most weight.

这篇关于如何为一个句子计算极性? (在情绪分析中)的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！