Some statistics say that between 9 and 15% of all active Twitter accounts are bots. Other estimates go up to a figure of 30% of all active accounts. The use of social bots for or in the context of election campaigns in the US and elsewhere has shown the significant impact that virtual echo chambers created by bots can have.

In Germany the present legal situation could be summarized as follows:

• The use of social bots for advertisement and campaigning purposes is admissible if it is clearly stated that an account or a post is automatized (= a bot) and the post is advertisement.
• If a company uses social bots for customer care for instance the mere fact that it is a bot responding to the customer request does not need to be disclosed.
• Injunctive action can be taken against operators of social bots that are infringing the above rules and their clients based on the Law Against Unfair Competition (UWG).

The legal situation is one thing. The question how we can discover social bots and how we can find the person or entity behind the bot is another thing.

The Indiana University has initiated the “Truthy” project, a research project aimed to study information diffusion in social media. Part of the project is the botometer software (https://botometer.iuni.iu.edu/#!/).

Botometer checks the activity of a Twitter account and gives it a score based on how likely the account is to be a bot. Higher scores are more bot-like. A good approach we think.