文本清洗基础

R 自然语言处理入门

Kasey Jones

Research Data Scientist

俄罗斯推文数据集

300万条俄罗斯水军推文

"俄罗斯水军推文"数据集由 fivethirtyeight 提供，包含在 2016 年美国大选期间由机器人生成的 300 万条推文。

我们将探索前 20,000 条推文
数据包含推文、粉丝数、关注数、发布时间、账号类型等
适合主题建模、分类、命名实体识别等任务

¹ https://github.com/fivethirtyeight/russian-troll-tweets

最高频词

library(tidytext); library(dplyr)
russian_tweets %>%
  unnest_tokens(word, content) %>%
  count(word, sort = TRUE)

# A tibble: 44,318 x 2
   word      n
   <chr> <int>
 1 t.co  18121
 2 https 16003
 3 the    7226
 4 to     5279
 ...

移除停用词

tidy_tweets <- russian_tweets %>%
  unnest_tokens(word, content) %>%
  anti_join(stop_words)

tidy_tweets %>%
  count(word, sort = TRUE)

 1 t.co             18121
 2 https            16003
 3 http              2135
 4 blacklivesmatter  1292
 5 trump             1004
 ...

# A tibble: 1,149 x 2
   word        lexicon
   <chr>       <chr>  
 1 a           SMART  
 2 a's         SMART  
 3 able        SMART  
 4 about       SMART  
 5 above       SMART

自定义停用词

custom <- add_row(stop_words, word = "https", lexicon = "custom")
custom <- add_row(custom, word = "http", lexicon = "custom")
custom <- add_row(custom, word = "t.co", lexicon = "custom")

russian_tweets %>%
  unnest_tokens(word, content) %>%
  anti_join(custom) %>%
  count(word, sort = TRUE)

最终结果

# A tibble: 43,663 x 2
   word                 n
   <chr>            <int>
 1 blacklivesmatter  1292
 2 trump             1004
 3 black              781
 4 enlist             764
 5 police             745
 6 people             723
 7 cops               693

词干提取（Stemming）

enlisted ---> enlist
enlisting ---> enlist

library(SnowballC)
tidy_tweets <- russian_tweets %>%
  unnest_tokens(word, content) %>%
  anti_join(custom)
# Stemming
stemmed_tweets <- tidy_tweets %>%
  mutate(word = wordStem(word))

词干提取结果

# A tibble: 38,907 x 2
   word               n
   <chr>          <int>
 1 blacklivesmatt  1301
 2 cop             1016
 3 trump           1013
 4 black            848
 5 enlist           809
 6 polic            763
 7 peopl            730

示例时间。

R 自然语言处理入门