“Finding New Connections on Bluesky: A Data-Driven Approach”

by jsendak | Nov 24, 2024 | DS Articles

If there is one development at the moment which I full heartedly enjoy reading about it’s that the remains of what was once called Twitter is seeing a large E𝕏odus.
Since a certain billionaire has taken over that platform, it has continuously become worse and I was hoping that politcians, media outlets and my fellow social scientists would come to Bluesky instead, which is apparently exactly what is happening now.
So after a lot of disappointment with world events this year, my wish that Bluesky would become Twitter’s heir, seems to come true.
The reasons I like Bluesky so much are that it connects me with a peer group that is spread around the world, like Twitter once did, but that it is built on open source infrastructure, which not only makes it billionaire proof, but also incredibly easy to tap into the data.
Overall it is just a place of joy right now and thanks to how serious the developers took community moderation, I’m hopeful that it will stay this way.

However, that led to a problem this week which can only be described as ‘incredibly first world’.
I was getting too many notifications about new followers!
So many that it became impossible to go through all of them and check whom to follow back.
My approach to solving the problem?
Using R and the atrrr package I created with friends ealiers this year.

library(atrrr)
library(tidyverse)
my_followers <- get_followers("jbgruber.bsky.social", limit = Inf) |>
  # remove columns containing more complex data
  select(-ends_with("_data"))
my_follows <- get_follows("jbgruber.bsky.social", limit = Inf) |>
  select(-ends_with("_data"))
not_yet_follows <- my_followers |>
  filter(!actor_handle %in% my_follows$actor_handle)

follows_of_follows <- my_follows |>
  pull(actor_handle) |>
  # iterate over follows getting their follows
  map(function(handle) {
    get_follows(handle, limit = Inf, verbose = FALSE) |>
      mutate(from = handle)
  }, .progress = interactive()) |>
  bind_rows() |>
  # not sure what this means
  filter(actor_handle != "handle.invalid")

follows_of_follows_count <- follows_of_follows |>
  count(actor_handle, name = "n_following", sort = TRUE)
follows_of_follows_count
## # A tibble: 160,440 × 2
##    actor_handle              n_following
##    <chr>                           <int>
##  1 jbgruber.bsky.social              400
##  2 claesdevreese.bsky.social         352
##  3 rossdahlke.bsky.social            292
##  4 alessandronai.bsky.social         285
##  5 favstats.eu                       263
##  6 feloe.bsky.social                 263
##  7 jamoeberl.bsky.social             246
##  8 brendannyhan.bsky.social          226
##  9 fgilardi.bsky.social              225
## 10 dfreelon.bsky.social              224
## # ℹ 160,430 more rows

popular_among_follows <- not_yet_follows |>
  left_join(follows_of_follows_count, by = "actor_handle") |>
  filter(n_following > 30)

probably_interesting_content <- not_yet_follows |>
  filter(!is.na(actor_description)) |>
  filter(str_detect(actor_description, regex("#commsky|#polsky|#rstats",
                                             ignore_case = TRUE)))

popular_not_yet_follows <- not_yet_follows |>
  mutate(followers_count = get_user_info(actor_handle)$followers_count) |>
  filter(followers_count > 1000)

lets_follow <- bind_rows(
  popular_among_follows,
  probably_interesting_content,
  popular_not_yet_follows
) |>
  distinct(actor_handle) |>
  pull(actor_handle)

follow(lets_follow)

walk(
  paste0("https://bsky.app/profile/", lets_follow),
  browseURL
)

popular_among_follows2 <-  follows_of_follows_count |>
  filter(!actor_handle %in% my_follows$actor_handle) |>
  filter(n_following > 30)

Continue reading: So many new people on Bluesky! Who should I follow?

Examining the Potential Effects and Implications of the Transition from Twitter to Bluesky

As the remains of the once-popular social media platform, Twitter, experience a present E𝕏odus, a parallel move towards the open-source platform, Bluesky, is apparent. This shift is not only noticeably observed in the actions of social scientists, media outlets, and politicians, but also, supported by a large number of users who might prioritize the open-source infrastructure of Bluesky over Twitter.

A Better Social Media Experience

Bluesky is rising in popularity and preference as it offers an experience quite close to Twitter’s golden days – efficiently connecting users with a peer group scattered around the globe, with an emphasis on ease of data access. Such ease of data access is attributed to Bluesky’s underlying open-source architecture, which manages to keep the platform immune from the influences of billionaires, simultaneously promoting community moderation.

Although the increasing engagement has recently led to situations where users might feel overwhelmed by the notification count from new followers, it still reflects the platform’s growing popularity.

Edging Towards Personalized Experience

A solution proposed to efficiently manage this problem is crafted around using R, a programming language, and a package called ‘atrrr’ to create filters based on personalized criteria. One of the algorithms designed using ‘atrrr’ first determines who follows a user without being followed back. The output list is then filtered based on popularity among fellow followers, content relevance or specific keywords in bio, and the amount of followers they have. These filters help list potential followers that would ideally enrich the user’s feed.

Actionable Advice Based on the Transition Implications

Evidently, the advent of Bluesky seems to offer a promising alternative for Twitter users and is seen as a refreshing development in the sphere of social media. However, the issue of efficiently managing a growing number of followers is a challenge that must be addressed. The long-term implications of this transition may include some of the following:

1. The continuous exodus from Twitter to Bluesky could signify a broader shift in priority towards open-source platforms. Platforms that can guard against negative billionaire influence and offers straightforward data access could soon be the norm.
2. As these platforms grow, the need for efficient tools that can manage increasing engagement becomes absolutely crucial. This means there could be a surge in demand for social data analysis and manipulation packages/tools such as ‘atrrr’.
3. As users become more selective about who they follow, more personalized algorithms will be needed to monitor content relevance. This signifies an increased emphasis on AI and data science expertise in social media planning and development.

Advice for Bluesky Users

Those feeling overwhelmed by follower notifications on Bluesky might consider using ‘atrrr’ to help manage the influx. Notably, ‘atrrr’ allows users to filter potential followers they might want to follow back based on their customized criteria, significantly enhancing their social media experience.

For Bluesky newbies or individuals seeking to expand their network, the website Bluesky Directory offers starter packs ordered by topics to help find interesting accounts. It could be a good starting point to navigate the platform and establish a strong presence.

For Learners and Developers

Educational resources and tutorials on using ‘atrrr’ can be found on the package’s website. To improve and build upon the current version of ‘atrrr’, the creators warmly welcome suggestions, issues, or ideas that could enhance the package. This is an opportunity for positive collaboration and an open invitation for individuals wanting to contribute to a relevant and influential project.

A Conclusion on the Transition

In conclusion, the transition from Twitter to Bluesky seems to be a reflection of user’s desire for a better social media experience. Developers and social media strategists can build upon this shift, focusing on creating tools and algorithms that help manage growing engagement and deliver personalized, enriching content. Bluesky seems to have started its journey on the right note. The successful management of large-scale user migration and active participation of its users in development might write the success story for Bluesky, making it an ideal successor to Twitter.

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