我正在尝试学习如何使用Twitter数据进行一些文本分析。创建一个术语频率矩阵时，我正在遇到问题。我用西班牙文本(带有特殊字符(创建语料库，没有问题。
但是，当我创建术语频率矩阵(带有Quanteda或TM库(时，西班牙字符并未按预期显示(而不是看到Canción，我看到Canciãnn(。
关于如何获得术语频率矩阵以使用正确字符存储文本的任何建议？
谢谢您的任何帮助。
注意：我更喜欢使用Quanteda库，因为最终我将创建一个WordCloud，并且我认为我更好地理解了该库的方法。我也在使用Windows机器。
我尝试编码(TW2(＆lt; - " UTF-8"，没有运气。
library(dplyr)
library(tm)
library(quanteda)
#' Creating a character with special Spanish characters:
tw2 <- "RT @None: Enmascarados, si masduro chingán a tarek. Si quieres ahora, la aguantas canción . https://t."
#Cleaning the tweet, removing special punctuation, numbers http links,
extra spaces:
clean_tw2 <- tolower(tw2)
clean_tw2 = gsub("&", "", clean_tw2)
clean_tw2 = gsub("(rt|via)((?:\b\W*@\w+)+)", "", clean_tw2)
clean_tw2 = gsub("@\w+", "", clean_tw2)
clean_tw2 = gsub("[[:punct:]]", "", clean_tw2)
clean_tw2 = gsub("http\w+", "", clean_tw2)
clean_tw2 = gsub("[ t]{2,}", "", clean_tw2)
clean_tw2 = gsub("^\s+|\s+$", "", clean_tw2)
# creates a vector with common stopwords, and other words which I want removed.
myStopwords <- c(stopwords("spanish"),"tarek","vez","ser","ahora")
clean_tw2 <- (removeWords(clean_tw2,myStopwords))
# If we print clean_tw2 we see that all the characters are displayed as expected.
clean_tw2
#'Create Corpus Using quanteda library
corp_quan<-corpus(clean_tw2)
# The corpus created via quanteda, displays the characters as expected.
corp_quan$documents$texts
#'Create Corpus Using TD library
corp_td<-Corpus(VectorSource(clean_tw2))
#' Remove common words from spanish from the Corpus.
#' If we inspect the corp_td, we see that the characters and words are displayed correctly
inspect(corp_td)
# Create the DFM with quanteda library.
tdm_quan<-dfm(corp_quan)
# Here we see that the spanish characters are displayed incorrectly for Example: canción = canción
tdm_quan
# Create the TDM with TD library
tdm_td<-TermDocumentMatrix(corp_td)
# Here we see that the Spanish characters are displayed incorrectly (e.g. canción = canciÃ), and "si" is missing.
tdm_td$dimnames$Terms
在Windows平台上创建DFM时，看起来Quanteda(和TM(正在失去编码。在这个问题上的问题中，同样的问题在毫无疑问的代币中也会发生。现在可以正常工作，并且quanteda的tokens工作正常。如果我在dfm的@Dimnames$features上执行UTF-8或latin1编码，则获得正确的结果。
....
previous code
.....
tdm_quan<-dfm(corp_quan)
# Here we see that the spanish characters are displayed incorrectly for Example: canción = canción
tdm_quan
Document-feature matrix of: 1 document, 8 features (0% sparse).
1 x 8 sparse Matrix of class "dfm"
features
docs enmascarados si masduro chingán quieres aguantas canción t
text1 1 2 1 1 1 1 1 1
如果执行以下操作：
Encoding(tdm_quan@Dimnames$features) <- "UTF-8"
tdm_quan
Document-feature matrix of: 1 document, 8 features (0% sparse).
1 x 8 sparse Matrix of class "dfm"
features
docs enmascarados si masduro chingán quieres aguantas canción t
text1 1 2 1 1 1 1 1 1
让我猜...您在使用Windows吗？在MacOS上，它可以正常工作：
clean_tw2
## [1] "enmascarados si masduro chingán si quieres aguantas canción"
Encoding(clean_tw2)
## [1] "UTF-8"
dfm(clean_tw2)
## Document-feature matrix of: 1 document, 7 features (0% sparse).
## 1 x 7 sparse Matrix of class "dfm"
## features
## docs enmascarados si masduro chingán quieres aguantas canción
## text1 1 2 1 1 1 1 1
我的系统信息：
sessionInfo()
# R version 3.4.4 (2018-03-15)
# Platform: x86_64-apple-darwin15.6.0 (64-bit)
# Running under: macOS High Sierra 10.13.4
#
# Matrix products: default
# BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
# LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib
#
# locale:
# [1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
#
# attached base packages:
# [1] stats graphics grDevices utils datasets methods base
#
# other attached packages:
# [1] tm_0.7-3 NLP_0.1-11 dplyr_0.7.4 quanteda_1.1.6