Cannot identify Chinese character in word2vec - r

Question

I am a new comer on word embedding and write a simple program to capture the message from my whatsapp to try the word2vec function in R. Everything works well and I can successfully generate the embedding matrix with the Chinese character showed in the correct way. However, when I use the predict, type=nearest function, the program shows that the Chinese character is not in the dictionary (there is no such problem if the character is English). Is it a problem related to encoding?
My code is as follows:
library(tidyverse)
library(dplyr)
library(rwhatsapp)
library(word2vec)
chat<-rwa_read("C:/Users/peace/Desktop/_chat.txt")
temp<-post_seg$text
words<-word2vec(temp,dim=15,encoding ="UTF-8")
embedding <- as.matrix(words)
nn1 <- predict(words, c("cpc"), type = "nearest", top_n = 5,encoding ="UTF-8")
nn2 <- predict(words, c("夠"), type = "nearest", top_n = 5,encoding ="UTF-8")
Error message shown when nn2 is run:
Error in w2v_nearest(object$model, x = x, top_n = top_n, ...) :
Could not find the word in the dictionary: 夠
But it works well when running the embedding matrix and nn1:
方猛 -0.1368161887 -1.1562500000 -1.461319923
夠 -0.8252676129 -1.5346769094 -1.077145815
cpc -0.1976414174 0.3481757045 0.275686920
[ reached getOption("max.print") -- omitted 2410 rows ]
> nn1
$cpc
term1 term2 similarity rank
1 cpc storeid 0.9780686 1
2 cpc ns 0.9569275 2
3 cpc term 0.8783157 3

Answer 1

Try this way
library(tidyverse)
library(dplyr)
library(rwhatsapp)
library(word2vec)
chat<-rwa_read("C:/Users/peace/Desktop/_chat.txt")
temp<-post_seg$text
words<-word2vec(temp,dim=15,encoding ="UTF-8")
Sys.setlocale(category = 'LC_ALL', locale = 'C')
embedding <- as.matrix(words)
nn2 <- predict(words, c("夠"), type = "nearest", top_n = 5,encoding ="UTF-8")
Sys.setlocale(); Sys.getlocale()
nn2