Glossary of Platform Law and Policy Terms


Cite this article as:
Luã Fergus Cruz and Laila Lorenzon (17/12/2021). Bot. In Belli, L.; Zingales, N. & Curzi, Y. (Eds.), Glossary of Platform Law and Policy Terms (online). FGV Direito Rio.

Authors: Luã Fergus and Laila Lorenzon

‘Bot’ is a tech slang for ‘robot’. In this sense, they share the same conceptual core: a reprogrammable machine built to perform a variety of tasks (RIA, n.d.)1. In the specific case of online bots, they are labeled as automatic or semi-automatic computer programs that run over the Internet (Franklin; Graesser, 19962; Gorwa; Guilbeault, 20183).

One of a bot 4main asset is its ability to perform simple and repetitive tasks faster than a human, and at scale – with some arguing that the most repetitive tasks in human jobs (and some jobs entirely)5 will be soon replaced by this increasing software automation (Bort, 2014)6.

Bots’ activities online may have impressive proportions, and, in this perspective, it is worth noting that 37.9% of total internet traffic in 2018 was carried out by bots, with 53.4% of them coming from the United States (Roberts, 2020)7.

Some experts and companies divide bots into two broad categories: ‘benevolent’ and ‘malicious bots’ (Jones, 20158; Cloudfare, n.d.9). The first category is subdivided into: ‘social bots’ simulate human behavior in automated interactions to manage social media accounts; ‘commercial bots’, usually used to increase online engagement in companies or as ‘chatbots’ to autonomously conduct a conversation instead, especially with consumers; ‘web crawlers’ bots, also known as ‘Google bots’, which scan content on webpages all over the Internet and gather useful information; ‘entertainment bots’, that are designed to be appreciated aesthetically (‘art bots’) or as characters to play against (‘game bots’); and, finally, ‘helpful’ or ‘informational bots’, that surface helpful information and usually push notifications and breaking news stories. 

The examples mentioned above are usually utilized to help/optimize human actions and tasks. In the opposite way, ‘malicious bots’ can be: ‘scrapers bots’ that are designed to steal content or vast amounts of data; ‘spam bots’, designed to automatically circulate unrequested content around the web in order to drive traffic to the spammer’s website, fill out forms automatically, congest servers or just cause disturbance; ‘scalper bots’, also known as automated purchasing, that are designed to purchase sought-after products and services; and ‘hacker bots’, that exploit security vulnerabilities to distribute malware, deceive individual people and attack websites or entire networks. In this latter case, devices that are affected are called ‘zombies’ and infected networks, ‘botnets’, a combination of ‘robot’ and ‘network’. These ‘botnets’ are programmed to perform mischievous tasks such as DDoS attacks, theft of confidential information, click fraud, cyber-sabotage, and cyber-warfare. For example, in September 2016, a botnet called Mirai was responsible for one of the biggest cyber-attacks in history when it launched a DDoS attack on the servers of Dyn, one of the primary DNS providers, which resulted in a blackout for various internet services (Antonakakis et al., 2017)10. Finally, a type of malicious bot that has pervasively dominated digital policy debates recently is the ‘impersonators bots’, a type of bot that mimics human behavior predominantly to manipulate public opinion, spread disinformation, and exercise social control (Bessi; Ferrara, 201611; Howard et al., 201812). 


  1. Robotic Industries Association (n.d.). Defining The Industrial Robot Industry and All It Entails. Available at:
  2. Franklin, S., Graesser, A. (1996). Is it an Agent, or just a Program? A Taxonomy for Autonomous Agents. In: International workshop on agent theories, architectures, and languages. 21-35. Springer, Berlin, Heidelberg.
  3. Gorwa, R., Guilbeault, D. (2020). Unpacking the social media bot: A typology to guide research and policy. Policy & Internet. 12(2). 225-248.
  4. Botnerds. Types of Bots: An Overview. Available at:
  5. Delaney, K. J. (2017). The robot that takes your job should pay taxes, says Bill Gates. Quartz.
  6. Bort, J. (2014). Bill Gates: People don’t realize how many jobs will soon be replaced by Software Bots. The Business Insider, USA.
  7. Roberts, E. (2020). Bad bot report 2020: Bad bots strike back. Imperva blog.
  8. Jones, S. (2015). How I learned to stop worrying and love the bots. Social Media+ Society. 1(1).
  9. Cloudflare. What is a bot? Available at:
  10. Antonakakis M., et al. (2017). Understanding the Mirai Botnet. In: 26th {USENIX} security symposium. {USENIX} Security 17. 1093-1110.
  11. Bessi, A., Ferrara, E. (2016). Social bots distort the 2016 US Presidential election online discussion. First Monday. 21(11-7).
  12. Howard, P. N., Woolley, S., Calo, R. (2018). Algorithms, bots, and political communication in the US 2016 election: The challenge of automated political communication for election law and administration. Journal of information technology & politics. 15(2). 81-93.

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