December 2nd, 2021
Hello! This is Becca, the new junior software developer at Datawrapper. You can get to know me better on my Say Hi to Rebecca article. Another map for you this week, but on more of a somber note. Please give it a look, and don’t be afraid to delve into the stories.
What factors do you consider when moving to a new place? Perhaps you think about what the nightlife is like, or how hot it is, or whether you’ll find a place of worship. Of course, different factors matter to different people. For a member of the LGBT+ community, one important factor to consider is personal safety.
When I recently moved to Berlin, I didn’t worry too much about safety; my perception of Berlin was that of an open, queer-friendly city. I knew it had a vibrant gay culture and nightlife, as well as spaces for examining history such as the Schwules Museum or the gay memorial in Tiergarten for those persecuted under Nazism. And since I arrived, this perception has never been contradicted.
But I don’t want to take that reputation for granted. As in any city, not everyone agrees and not everyone is tolerant — and even a statistically small amount of violence still has a big effect on its victims. In the map below, you can see 373 stories of violence towards the queer community in Berlin, collected over the last seven years. The data comes from the Berlin Register, a website that tracks discriminatory incidents and right-wing extremists. As the site is based on self-reports, and only incidents with a reported location are shown here, the actual number of incidents can be assumed to be far larger.
The incidents were classified into five categories: internet-based, propaganda and vandalism (for example, homophobic speeches or damaging of memorials), structural discrimination (for example, in the workplace), verbal harassment, and physical assault. I found it surprising that the most common category by far was physical assault. I would have expected most of the incidents to fall into the propaganda or verbal categories, as these are more subtle (but by no means less damaging) forms of violence. However, I'm cautious about drawing any conclusions from this observation, as it's possible that more extreme crimes are more likely to be self-reported.
One thing that stood out to me was how many of these incidents mentioned far-right political parties, including the NPD (National Democratic Party of Germany) and AfD (Alternative for Germany). A 2020 report by the LSVD, a German LGBT+ rights organization, found that around 35% of anti-LGBT+ hate crimes in Germany had a clear right-wing affiliation (with around 59% of cases having no identifiable ideology). Of course, this isn't a specifically German trend. Anti-LGBT+ hate speech is used by far-right parties across Europe, and Germany actually rates quite well on legal protections for LGBT+ people — 16th out of 49 countries, according to a 2021 ranking by the advocacy group ILGA-Europe.
This map can't tell us how safe or unsafe Berlin is — it's just too small and limited a sample for that. I can however say with complete conviction that every case is one too many, and I would be very surprised if the stories told on this map didn't leave you upset and angry as they did with me. I will leave you with a quote from the aforementioned LSVD report:
If before every loving glance, before an embrace, before a kiss in public, the surroundings must first be checked; if people cannot move safely in public space; if they avoid certain places for fear of violence, or take their bicycles instead of public transport to avoid becoming the victims of homophobic and transphobic incidents — then that is a serious restriction of freedom.
These incidents were scraped from the Berlin Register website and organized by Filipe Serro, who published the results on GitHub. I translated the stories from German to English using the site DeepL, which may have resulted in some grammatical errors. If you would like to read the original texts in German, you can find them in Filipe's project.
Sometimes multiple stories have been reported at the same location, which makes it hard to distinguish their dots on the map. This is where jittering (explained by Lisa in this Weekly Chart) comes in. I jittered only the repeated locations by subtracting a small random number from their latitude and longitudes.
That's it from me this week! I now pass the Weekly Chart baton to Eddie from our support team here at Datawrapper.
If you would like to know more, here are a few links on this week's topics: