As our interpersonal interactions occur more and more in the digital realm, the negative byproducts seem to grow in fierceness and persistence. Even the most casual of social media users is likely to have experienced some form of hostility, mistruths, or aggressive trolling.

Just how bad is it? A recently conducted census representative survey by Dalia Research finds that 34% of Germans using social media have read articles or news that were intentionally misleading or not truthful (fake news), 16% have received offensive messages or comments from someone they don’t know, 14% have received sexually offensive messages, and 3% have received threats. 16% of Germans have also reported a user for abuse on social media. Overall, men report higher instances of offensive comments, threats and fake news overall, while German women report experiencing more sexual harassment than men (16% v. 12%).

 

The increasing levels of internet hate speech, harassment and fake news has led Germany to create the NetzDG law, which requires social media sites like Twitter, Reddit and Youtube to remove hate speech, threats, fake news and other controversial content within 24 hours. The consequence of failing to remove banned content: up to 50 million euros in fines. As a result, social media companies in Germany have found ways to comply to the new law. For instance, Facebook has two deletion centers in Germany with 1,200 employees solely dedicated to monitoring content. While some applaud the law as being among the first of its kind to take precautionary steps against the spread of hate speech and fake news, NetzDG has also come under scrutiny from free speech advocates who say censorship shouldn’t be left in the hands of private companies. While the law was developed by the Social Democrats, opponents to the NetzDG come from all sides of the political spectrum, including the Free Democratic Party (FDP), the Green Party, and the Alternative for Germany (AfD).

Yet, when given a short summary of the censorship policy*, German respondents showed overwhelming support: 67% of Germans said they strongly approve of the policy and 20% somewhat approve for 87% in total. 7% neither approve or disapprove, and only 5% disapprove. According to Dalia’s study, such a policy would also fare well in France, the UK and the US. Respondents from France and the UK approve of the policy at 82%. 69% of Americans approve of the policy too, however only 46% of Americans strongly approve, compared to 57% in France and 56% in the UK.

*“As of 2018, German law states that if social media firms like Twitter, Reddit, and Youtube do not remove hate speech, threats, fake news or other controversial content within 24 hours, they will be fined.”

 

Takeaways:

First, these results should be taken with a grain of salt. It is highly possible that due to self-selection bias of social media users, the participants in this survey are more likely to come across inflammatory online content than most. However, the results do show that there is great support for a policy like NetzDG, in theory. In practice though, support is undoubtedly more complicated. Most people seem to agree with the idea of monitoring and removing fake news and harmful content, but the real question is who should be the arbitrator with the responsibility of classifying content as harmful or legitimate?

 

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About the survey

This report presents an overview of a study conducted by Dalia Research in March 2018 on public opinion of social media censorship across internet connected respondents in Germany, France, the US, and the UK. The total sample size is n=2.021 (Germany=505, France=508, UK=500, US=508). The total sample takes into account the current population distributions with regard to age (14-65 years), gender and region/country.

In order to obtain census representative results, the data were weighted based upon Eurostat statistics. The target weighting variables were age, gender, level of education (as defined by ISCED (2011) levels 0-2, 3-4, and 5-8), and degree of urbanization (rural and urban). An iterative algorithm was used to identify the optimal combination of weighting variables based on sample composition within each country. An estimation of the overall design effect based on the distribution of weights was calculated at 1 at the global level. Calculated for a sample of this size and considering the design-effect, the margin of error would be +/- 4.4% at a confidence level of 95%.

 

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