7.2. Origins of trolling# While the term “trolling” in the sense we are talking about in this chapter comes out of internet culture, the type of actions that we now call trolling have been happening as far back as we have historical records.
I thought it was interesting that trolling existed long before the internet. The internet just makes it easier for these behaviors to spread and reach more people than they could in the past.
repository open issue .md .pdf Contents 7.4.1. Reflection questions Responding to trolls? Contents 7.4.1. Reflection questions 7.4. Responding to trolls?# One of the traditional pieces of advice for dealing with trolls is “Don’t feed the trolls,” which means that if you don’t respond to trolls, they will get bored and stop trolling. We can see this advice as well in the trolling community’s own “Rules of the Internet”: Do not argue with trolls - it means that they win But the essayist Film Crit Hulk argues against this in Don’t feed the trolls, and other hideous lies. That piece argues that the “don’t feed the trolls” strategy doesn’t stop trolls from harassing: Ask anyone who has dealt with persistent harassment online, especially women: [trolls stopping because they are ignored] is not usually what happens. Instead, the harasser keeps pushing and pushing to get the reaction they want with even more tenacity and intensity. It’s the same pattern on display in the litany of abusers and stalkers, both online and off, who escalate to more dangerous and threatening behavior when they feel like they are being ignored. Film Crit Hulk goes on to say that the “don’t feed the trolls” advice puts the burden on victims of abuse to stop being abused, giving all the power to trolls. Instead, Film Crit Hulk suggests giving power to the victims and using “skilled moderation and the willingness to kick people off platforms for violating rules about abuse”
This section made me rethink the advice to “not feed the trolls.” Ignoring harassment doesn’t always make it stop, and it can end up putting all the responsibility on the person being targeted. Strong moderation seems more fair because it holds trolls accountable instead of asking victims to deal with it on their own.
6.3.1. Inauthentic Behaviors# Inauthentic behavior is when the reality doesn’t match what is being presented. Inauthenticity has, of course, existed throughout human history, from Ea-nasir complaining in 1750 BCE that the copper he ordered was not the high quality he had been promised, to 1917 CE in England when Arthur Conan Doyle (the author of the Sherlock Holmes stories) was fooled by photographs that appeared to be of a child next to fairies.
These historical examples show that inauthentic behavior is not new, but has long been part of human communication. What changes in digital contexts is the scale and speed at which inauthenticity can spread, especially when platforms and automated systems amplify misleading representations.
6.3. Inauthenticity# In 2016, the Twitter account @Sciencing_Bi was created by an anonymous bisexual Native American Anthropology professor at Arizona State University (ASU). She talked about her experiences of discrimination and about being one of the women who was sexually harassed by a particular Harvard professor. She gained a large Twitter following among academics, including one of the authors of this book, Kyle. Separately, in 2018 during the MeToo movement, one of @Sciencing_Bi’s friends, Dr. BethAnn McLaughlin (a white woman), co-founded the MeTooSTEM non-profit organization, to gather stories of sexual harassment in STEM (Science, Technology, Engineering, Math). Kyle also followed her on Twitter until word later spread of Dr. McLaughlin’s toxic leadership and bullying in the MeTooSTEM organization (Kyle may have unfollowed @Sciencing_Bi at the same time for defending Dr. McLaughlin, but doesn’t remember clearly). Then, in April 2020, in the early days of the COVID pandemic, @Sciencing_Bi complained of being forced to teach in person at ASU when it wasn’t safe, and then began writing about their COVID symptoms.
This case illustrates how perceptions of authenticity on social media are often built through personal narratives and shared experiences. When accounts gain trust through identity claims and moral authority, questions of inauthenticity can have especially high stakes, affecting not only credibility but also the communities and causes connected to that account.
The 1980s and 1990s also saw an emergence of more instant forms of communication with chat applications. Internet Relay Chat (IRC) lets people create “rooms” for different topics, and people could join those rooms and participate in real-time text conversations with the others in the room.
IRC illustrates an early shift from one-to-one messaging toward real-time, group-based communication organized around shared topics. The structure of chat rooms anticipates many features of modern online communities, while still relying on relatively minimal automation compared to today’s platform-driven social spaces.
One of the early ways of social communication across the internet was with Email, which originated in the 1960s and 1970s. These allowed people to send messages to each other, and look up if any new messages had been sent to them.
Highlighting email as an early form of online social communication helps put modern platforms in historical context. Unlike today’s algorithm-driven feeds, early email systems were largely user-initiated, which shows how automation and visibility have become much more central to social interaction over time.
There are several options for how to save dates and times. Some options include a series of numbers (year, month, day, hour, minute, and second), or a string that with all of those pieces of information written out. Sometimes only the date is saved, with no time information, and sometimes the time information will include the timezone. Dates turn out to be one of the trickier data types to work with in practice. One of the main reasons for this is that what time or day it depends on what time zone you are in. So, for example, when Twitter tells me that the tweet was posted on Feb 10, 2020, does it mean Feb 10 for me? Or for the person who posted it? Those might not be the same. Or if I want to see for a given account, how much they tweeted “yesterday,” what do I mean by “yesterday?” We might be in different time zones and have different start and end times for what we each call “yesterday.”
This discussion shows that dates and times are not neutral data, but depend on context such as time zones and perspective. When platforms define concepts like “today” or “yesterday,” they are making design choices that can shape how activity is measured and interpreted, which becomes especially important when analyzing user behavior or automated posting.
When computers store numbers, there are limits to how much space is can be used to save each number. This limits how big (or small) the numbers can be, and causes rounding with floating-point numbers. Additionally, programming languages might include other ways of storing numbers, such as fractions, complex numbers, or limited number sets (like only positive integers).
This section highlights how numerical limits are built into computer systems rather than being purely abstract. These constraints matter because rounding or restricted number types can affect how automated systems make decisions, especially at scale, where small numerical differences may accumulate into meaningful outcomes.
Computers typically store text by dividing the text into characters (the individual letters, spaces, numerals, punctuation marks, emojis, and other symbols). These characters are then stored in order and called strings (that is a bunch of characters strung together, like in Fig. 4.6 below).
This technical explanation is helpful because it shows how human language is reduced to structured data that computers can process. When social media platforms treat text as strings, meaning and emotional context can be lost or oversimplified, which becomes ethically important when automated systems moderate content, detect harassment, or make decisions about visibility and punishment.
Sometimes in programming, we want to group several steps (i.e., statements) together. When we group these steps together we call it a code “block.” These blocks of code often used with conditionals (e.g., if this condition is true, do these five steps), and with loops (e.g., for each of these items, do these five steps).
Explaining code blocks this way helps clarify how automated actions are grouped and repeated in bot behavior. When blocks are combined with conditionals and loops, it becomes clear how a single decision rule can lead to large-scale repeated actions, which is especially relevant when considering how bots can amplify content or behavior across platforms.
In order to understand how a bot is built and can work, we will now look at the different ways computer programs can be organized. We will cover a bunch of examples quickly here, to hopefully give you an idea of many options for how to write a program. Don’t worry if you don’t follow all of it, as we will go back over these one at a time in more detail throughout the book. In this section, we will not show actual Python computer programs (that will be in the next section). Instead, here we will focus on what programmers call “psuedocode,” which is a human language outline of a program. Psuedocode is intended to be easier to read and write. Pseudocode is often used by programmers to plan how they want their programs to work, and once the programmer is somewhat confident in their pseudocode, they will then try to write it in actual programming language code.
This explanation of pseudocode is helpful because it lowers the barrier to understanding how bots are structured without requiring prior programming knowledge. Framing pseudocode as a planning and thinking tool emphasizes that building bots is not just a technical process, but also a conceptual one where ethical choices can be made early, before code is even written.
This means that media, which includes painting, movies, books, speech, songs, dance, etc., all communicates in some way, and thus are social. And every social thing humans do is done through various mediums. So, for example, a war is enacted through the mediums of speech (e.g., threats, treaties, battle plans), coordinated movements, clothing (uniforms), and, of course, the mediums of weapons and violence.
I find this example effective because it expands the idea of media beyond digital platforms and shows that media is embedded in almost all human action. By framing war itself as something enacted through multiple mediums, this passage highlights how communication, symbols, and coordination are inseparable from power and violence, which is especially relevant when thinking about how modern social media can amplify or legitimize conflict.