Bluesky and the german Bubble

I had already reported on Bluesky the other day. It is portrayed in many places that it is more of a duet retreat. In fact, the percentage of German posts is in the single digits (thanks to Aurel Wünsch, who analysed this).

But how can one establish comparability? Since absolute numbers are difficult, let’s take an example from the local bubble: Here we have the “FotoVorschlag” (“photo suggestion”) who is active on X (aka Twitter), as well as on Bluesky. He posts a topic every day and those who are interested can then post a suitable picture of their own on the topic below it. What makes it exciting is that he posts at about the same time each day with the exact same text and hashtags (although these are “still” unnecessary on Bluesky).

I have now looked at the posts over a period of time, starting a few weeks before the Bluesky account even started. But let’s start with the systematics:

Synopsis of some Tweets and the pendant on Bluesky

(Fun fact: Here you can see the similarities between Bluesky and X quite clearly) I have picked out two that Fotovorschlag published on Bluesky and X on 23.10.2023 respectively. Note: You can’t see the number of replies directly on Bluesky, but only in the search.

Now I have measured the interactions, i.e. how many likes, replies and responses the respective post has received. I calculated these numbers on two dates and they are therefore related to a specific date. If you check them today, they may be slightly different. As of yesterday, Fotovorschlag on X has put a lock in front of it, so a direct comparison is no longer possible. So I have finished the measurement with this.

Disclaimer: Yes, I know that the empirical relevance is manageable as only the “bubbles” from the photo suggestion are compared here and no conclusion can be drawn about the totality.

Back to the numbers: In Excel it looks like this:

X vs. Bluesky: What happens? Trends of the innteractions for two months. Bluesky is rising, x is falling down.

The outliers are exciting: If the highest value of interactions on X reached 402 (the sum of all replies, retweets (at that time) and likes), this peak value on Blueksy is 589. So you can see that in a very, very short period of time the interest has shifted a lot from the bubble of “photo suggestion”.

If anyone is interested in the Excel with the raw data, please contact me.

Here is the article in German.

London Oxford Street

About Bubbles in Social Media


The terms “bubbles” and “bubbles” are popularly used and applied in social media. The question is asked:


All this talk of bubbles and bubbles, when did it end?


In many cases it is already considered overused. And here I have a different opinion: in my opinion, the functioning of muting and especially blocking is often misunderstood. First of all: everyone can and may use social media and Twitter as they see fit. There is no such thing as “wrong” and / or “right use”. Nevertheless, a few comments on how bubbles and bubbles are created:


Example on Twitter, which I am essentially referring to in this article, I have blocked 10 or 12 people myself (and for almost all of them I remember why) and have muted maybe 20 or 30 people who post your agenda prayerfully.


Others use the function of blocking differently: there used to be even block lists that individuals published and So these were uploaded by fellow social media users and they blocked the same people. Unreflectively. Just like that. Now tools like Megablock are used: This one seems handy: So, everyone who is of the same opinion is automatically blocked. This tool is extremely practical if you have published a book and are actually on a social media channel to promote it. Then you are not forced to discuss.


However, bubbles are created because “both sides” of an opinion use this technique: You surround yourself exclusively with the people with whom you are in harmony. In the long run, everything is nice and harmonious because everyone is in perfect sync. But then it is only a matter of self-created space, the personal bubble.
Another example:


Why does the fucking savings bank explain to me what LGBTQ+ means?

In fact, pride month seems to be a concentrated action where many companies participate. And at first glance, it has a “taint” when companies occupy such important topics. But on the other hand: we are in a bubble of social media users. A cool look at the comparison of the reach of Sascha Lobo vs. Apothekenumschau explains a lot: The latter has a reach that is roughly equivalent to umpteen times that of the former. So when the Sparkasse takes up the topic, it is carried by our balse and increases the social relevance and perception of these topics. We are quite alone on Twitter, and it makes sense to spread the word outside of Twitter about issues like LGBTQ+ (but also climate, etc.). In principle, I think it is presumptuous to want to define who is discussing what.

German Version here.