r - 如何使用sentimentr或qdap检测否定句

Question

我正在尝试从包含否定的医疗报告中提取(并最终分类)句子。一个例子是这样的:

samples<-c('There is no evidence of a lump','Neither a contusion nor a scar was seen','No inflammation was evident','We found generalised badness here')

我正在尝试使用 sentimentr 包，因为它似乎能够检测否定者。有没有一种方法可以仅使用否定器的检测来提取否定句(最好将其提取到新的数据框中以进行进一步的工作)？

使用qdap中的极性只是给出一个汇总统计数据，并且基于包括我不想包括的放大器和去放大器。

polarity(samples,negators = qdapDictionaries::negation.words)

      all total.sentences total.words ave.polarity sd.polarity stan.mean.polarity
1 all               4          24        0.213       0.254              0.842

我尝试了情感包如下:

extract_sentiment_terms(MyColonData$Endo_ResultText,polity_dt = lexicon::hash_sentiment_jockers, 连字符 = "")

这给了我中性、消极和积极的词:

   element_id sentence_id     negative positive
1:          1           1                      
2:          2           1         scar         
3:          3           1 inflammation  evident
4:          4           1      badness    found

但我确实在寻找包含否定词的句子仅而不解释情绪，因此输出是:

element_id sentence_id                          negative                    positive
1:          1           1     There is no evidence of a lump                 
2:          2           1     Neither a contusion nor a scar was seen       
3:          3           1     No inflammation was evident
4:          4           1                                               We found generalised badness here

Answer 1

我认为您只想根据否定符的存在对文本进行正面和负面分类，因此从词典中提取否定符应该会有所帮助。

samples<-c('There is no evidence of a lump','Neither a contusion nor a scar was seen','No inflammation was evident','We found generalised badness here')


polarity <- data.frame(text = samples, pol = NA)

polarity$pol <- ifelse(grepl(paste(lexicon::hash_valence_shifters[y==1]$x,collapse = '|'), tolower(samples)),'Negative','Positive')

polarity

                                     text      pol
1          There is no evidence of a lump Negative
2 Neither a contusion nor a scar was seen Negative
3             No inflammation was evident Negative
4       We found generalised badness here Positive

格式化OP:

reshape2::dcast(polarity,text~pol) 



                                     text Negative Positive
1 Neither a contusion nor a scar was seen Negative     <NA>
2             No inflammation was evident Negative     <NA>
3          There is no evidence of a lump Negative     <NA>
4       We found generalised badness here     <NA> Positive