我的data.frame
有周数,week
和文字评论text
。我想将week
变量视为我的分组变量,并对其进行一些基本的文本分析(例如qdap::polarity
)。一些评论文本有多个句子;但是,我只关心本周的“极端”极性。
如何在运行qdap::polarity
之前将多个文本转换链接在一起并遵守其警告消息?我可以使用tm::tm_map
和tm::tm_reduce
将变换链接在一起 - 在qdap
中是否存在可比较的内容?在运行qdap::polarity
和/或qdap::sentSplit
之前预处理/转换此文字的正确方法是什么?
以下代码/可重现示例中的更多详细信息:
library(qdap)
library(tm)
df <- data.frame(week = c(1, 1, 1, 2, 2, 3, 4),
text = c("This is some text. It was bad. Not good.",
"Another review that was bad!",
"Great job, very helpful; more stuff here, but can't quite get it.",
"Short, poor, not good Dr. Jay, but just so-so. And some more text here.",
"Awesome job! This was a great review. Very helpful and thorough.",
"Not so great.",
"The 1st time Mr. Smith helped me was not good."),
stringsAsFactors = FALSE)
docs <- as.Corpus(df$text, df$week)
funs <- list(stripWhitespace,
tolower,
replace_ordinal,
replace_number,
replace_abbreviation)
# Is there a qdap function that does something similar to the next line?
# Or is there a way to pass this VCorpus / Corpus directly to qdap::polarity?
docs <- tm_map(docs, FUN = tm_reduce, tmFuns = funs)
# At the end of the day, I would like to get this type of output, but adhere to
# the warning message about running sentSplit. How should I pre-treat / cleanse
# these sentences, but keep the "week" grouping?
pol <- polarity(df$text, df$week)
## Not run:
# check_text(df$text)
答案 0 :(得分:1)
您可以按警告中的建议运行execute="@this"
,如下所示:
sentSplit
请注意,我在github上提供了一个突破情绪包sentimentr,这是对 qdap 版本的速度,功能和文档的改进。这会在df_split <- sentSplit(df, "text")
with(df_split, polarity(text, week))
## week total.sentences total.words ave.polarity sd.polarity stan.mean.polarity
## 1 1 5 26 -0.138 0.710 -0.195
## 2 2 6 26 0.342 0.402 0.852
## 3 3 1 3 -0.577 NA NA
## 4 4 2 10 0.000 0.000 NaN
函数内部进行句子分割。下面的脚本允许您安装包并使用它:
sentiment_by