```r
top_terms <- tidy_lda %>%
  group_by(topic) %>%
  top_n(10, beta) %>%
  ungroup() %>%
  arrange(topic, -beta)

top_terms
```

```
## # A tibble: 240 x 3
##    topic term          beta
##    <int> <chr>        <dbl>
##  1     1 data        0.0449
##  2     1 soil        0.0368
##  3     1 moisture    0.0295
##  4     1 amsr        0.0244
##  5     1 sst         0.0168
##  6     1 validation  0.0132
##  7     1 temperature 0.0132
##  8     1 surface     0.0129
##  9     1 accuracy    0.0123
## 10     1 set         0.0116
## # … with 230 more rows
```