fix and regenerate vignette

newly strict tibble revealed that I was using `metadata(m)$journal` to
access `metadata(m)$journaltitle`.

Also, hide the progress report from `simplify_state` (invoked by
write_mallet_model).

vignettes/introduction.Rmd

@@ -177,7 +177,7 @@ The metadata supplied here as a parameter to `train_model` is not used in modeli
 
 Though this `r n_docs(m)`-corpus needs only minutes to model, it often takes hours or more to produce a topic model of even a moderately-sized corpus. You are likely to want to save the results. It is most convenient, I have found, to save both the richest possible MALLET outputs and user-friendlier transformations: many analyses need only the estimated document-topic and topic-word matrices, for example. For this reason, the default `write_mallet_model` function takes the results of `train_model` and outputs a directory of files.
 
-```{r message=F}
+```{r message=F, results="hide"}
 write_mallet_model(m, "modeling_results")
 ```
 
@@ -272,7 +272,7 @@ This is a "long" data frame suitable for plotting, which we turn to shortly. But
 To make this more general operation a little easier, I have supplied generalized aggregator functions `sum_row_groups` and `sum_col_groups` which take a matrix and a grouping factor. As a simple example, suppose we wanted to tabulate the way topics are split up between the two journals in our corpus:
 
 ```{r}
-journal <- factor(metadata(m)$journal)
+journal <- factor(metadata(m)$journaltitle)
 doc_topics(m) %>%
     sum_row_groups(journal) %>%
     normalize_cols()