```r
not_words <- bigrams_separated %>%
  filter(word1 == "not") %>%
  inner_join(AFINN, by = c(word2 = "word")) %>%
  count(word2, score, sort = TRUE) %>%
  ungroup()

not_words
```

```
## # A tibble: 245 x 3
##    word2   score     n
##    <chr>   <int> <int>
##  1 like        2    99
##  2 help        2    82
##  3 want        1    45
##  4 wish        1    39
##  5 allow       1    36
##  6 care        2    23
##  7 sorry      -1    21
##  8 leave      -1    18
##  9 pretend    -1    18
## 10 worth       2    17
## # … with 235 more rows
```