```{r}
#| eval: false
arrow::read_feather(
  "data/scratch/all_accounts.feather",
  col_select = c(
    "server", "username", "created_at",
    "last_status_at", "statuses_count",
    "has_moved", "bot", "suspended"
  )) %>%
  mutate(suspended = replace_na(suspended, FALSE)) %>%
  filter(!bot) %>%
  # TODO: what's going on here?
  filter(!is.na(last_status_at)) %>%
  # sanity check
  filter(created_at >= "2022-01-01") %>%
  filter(created_at < "2024-03-01") %>%
  # We don't want accounts that were created
  # and then immediately stopped being active
  filter(statuses_count > 1) %>%
  filter(!suspended) %>%
  filter(!has_moved) %>%
  filter(server == "mastodon.social") %>%
  #filter(last_status_at >= created_at) %>%
  mutate(created_month = format(created_at, "%Y-%m")) %>%
  group_by(created_month) %>%
  summarize(count=n()) %>%
  distinct(created_month, count) %>%
  ggplot(aes(x=created_month, y=count)) +
  geom_bar(stat="identity", fill="black") +
  labs(y="Count", x="Created Month") +
  theme_bw() + theme(axis.text.x = element_text(angle = 90, hjust = 1))
```

::: {.content-visible when-format="html"}

## Migrations in Online Communities 
The Twitter-Mastodon migration is only one entry in a series of migrations between online communities.

@burkeFeedMeMotivating2009 found that social learning could help explain the experiences of newcomers in the early days of Facebook. 


+ On Reddit, @newellUserMigrationOnline2021 found that the news aggregator had an advantage of potential competitors because of their catalogue of niche communities: people who migrated to alternative platforms tended to post most often proportionally in popular communities.

+ Fiesler on online fandom communities [@fieslerMovingLandsOnline2020]

+ TeBlunthuis on competition and mutalism [@teblunthuisIdentifyingCompetitionMutualism2022]

+ Work on "alt-tech" communities.

:::