20.1. What is Colonialism?# As most social media platforms are headquartered in a very set of locations (e.g., Silicon Valley in the US, and Beijing China), but used all over the world, it is important for us to look at the concepts and history of colonialism to understand what it means for social media to be controlled in these few places. So let’s start by defining colonialism and some related concepts. 20.1.1. Colonialism Defined# Colonialism is when one group or country subjugates another group, often imposing laws, religion, culture, and languages on that group, and taking resources from them. Colonialism is often justified by belief that the subjugated people are inferior (e.g., barbaric, savage, godless, backwards), and the superiority of the group doing the subjugation (e.g., civilized, advanced).

19.1. What is Capitalism?# Why do social media platforms make decisions that harm users? And why do social media platforms sometimes go down paths of self-destruction and alienating their users? Sometimes these questions can be answered by looking at the economic forces that drive decision-making on social media platforms, in particular with capitalism. So let’s start by defining capitalism. 19.1.1. Definition of Capitalism:# Capitalism is: “an economic system characterized by private or corporate ownership of capital goods, by investments that are determined by private decision, and by prices, production, and the distribution of goods that are determined mainly by competition in a free market” Merriam-Webster Dictionary In other words, capitalism is a system where: Individuals or corporations own businesses These business owners make what they want and set their own prices. They compete with other businesses to convince customers to buy their products. These business owners then hire wage laborers at predetermined rates for their work, while the owners get the excess business profits or losses

18.2. Online Criticism and Shaming# While public criticism and shaming have always been a part of human culture, the Internet and social media have created new ways of doing so. We’ve seen examples of this before with Justine Sacco and with crowd harassment (particularly dogpiling). For an example of public shaming, we can look at late-night TV host Jimmy Kimmel’s annual Halloween prank, where he has parents film their children as they tell the parents tell the children that the parents ate all the kids’ Halloween candy. Parents post these videos online, where viewers are intended to laugh at the distress, despair, and sense of betrayal the children express. I will not link to these videos which I find horrible, but instead link you to these articles: Jimmy Kimmel’s Halloween prank can scar children. Why are we laughing? (archived copy) Jimmy Kimmel’s Halloween Candy Prank: Harmful Parenting? We can also consider events in the #MeToo movement as at least in part public shaming of sexual harassers (but also of course solidarity and organizing of victims of sexual harassment, and pushes for larger political, organizational, and social changes).

18.1. Shame vs. Guilt in childhood development# Before we talk about public criticism and shaming and adults, let’s look at the role of shame in childhood. In at least some views about shame and childhood1, shame and guilt hold different roles in childhood development: Shame is the feeling that “I am bad,” and the natural response to shame is for the individual to hide, or the community to ostracize the person. Guilt is the feeling that “This specific action I did was bad.” The natural response to feeling guilt is for the guilty person to want to repair the harm of their action. In this view, a good parent might see their child doing something bad or dangerous, and tell them to stop. The child may feel shame (they might not be developmentally able to separate their identity from the momentary rejection). The parent may then comfort the child to let the child know that they are not being rejected as a person, it was just their action that was a problem. The child’s relationship with the parent is repaired, and over time the child will learn to feel guilt instead of shame and seek to repair harm instead of hide.

17.2. Crowd Harassment# Harassment can also be done through crowds. Crowd harassment has also always been a part of culture, such as riots, mob violence, revolts, revolution, government persecution, etc. Social media then allows new ways for crowd harassment to occur. Crowd harassment includes all the forms of individual harassment we already mentioned (like bullying, stalking, etc.), but done by a group of people. Additionally, we can consider the following forms of crowd harassment: Dogpiling: When a crowd of people targets or harasses the same person. Public Shaming (this will be our next chapter) Cross-platform raids (e.g., 4chan group planning harassment on another platform) Stochastic terrorism The use of mass public communication, usually against a particular individual or group, which incites or inspires acts of terrorism which are statistically probable but happen seemingly at random. See also: An atmosphere of violence: Stochastic terror in American politics In addition, fake crowds (e.g., bots or people paid to post) can participate in crowd harassment. For example:

17.1. Individual harassment# Individual harassment (one individual harassing another individual) has always been part of human cultures, bur social media provides new methods of doing so. There are many methods by which through social media. This can be done privately through things like: Bullying: like sending mean messages through DMs Cyberstalking: Continually finding the account of someone, and creating new accounts to continue following them. Or possibly researching the person’s physical location. Hacking: Hacking into an account or device to discover secrets, or make threats. Tracking: An abuser might track the social media use of their partner or child to prevent them from making outside friends. They may even install spy software on their victim’s phone. Death threats / rape threats Etc. Individual harassment can also be done publicly before an audience (such as classmates or family). For example: Bullying: like posting public mean messages Impersonation: Making an account that appears to be from someone and having that account say things to embarrass or endanger the victim. Doxing: Publicly posting identifying information about someone (e.g., full name, address, phone number, etc.). Revenge porn / deep-fake porn Etc.

16.3.1. “Solving” a “Problem”# When social media users work together, we can consider what problem they are solving. For example, for some of the Tiktok Duet videos from the virality chapter, the “problem” would be something like “how do we create music out of this source video” and the different musicians contribute their own piece to the solution. For some other examples: In the case of a missing hiker rescued after Twitter user tracks him down using his last-sent photo, the “problem” was “Where did the hiker disappear?” and the crowd investigated whatever they could to find the solution of the hiker’s location. In the case of Canucks’ staffer uses social media to find fan who saved his life, the “problem” was “Who is the fan who saved the Canucks’ staffer’s life?” and the solution was basically to try to identify and dox the fan (though hopefully in a positive way). In the case of Twitter tracks down mystery couple in viral proposal photos, the problem was “Who is the couple in the photo?” and the solution was again to basically dox them, though in the article they seemed ok with it.

16.3.1. “Solving” a “Problem”# When social media users work together, we can consider what problem they are solving. For example, for some of the Tiktok Duet videos from the virality chapter, the “problem” would be something like “how do we create music out of this source video” and the different musicians contribute their own piece to the solution. For some other examples: In the case of a missing hiker rescued after Twitter user tracks him down using his last-sent photo, the “problem” was “Where did the hiker disappear?” and the crowd investigated whatever they could to find the solution of the hiker’s location. In the case of Canucks’ staffer uses social media to find fan who saved his life, the “problem” was “Who is the fan who saved the Canucks’ staffer’s life?” and the solution was basically to try to identify and dox the fan (though hopefully in a positive way). In the case of Twitter tracks down mystery couple in viral proposal photos, the problem was “Who is the couple in the photo?” and the solution was again to basically dox them, though in the article they seemed ok with it.

16.1. Crowdsourcing Definition# When tasks are done through large groups of people making relatively small contributions, this is called crowdsourcing. The people making the contributions generally come from a crowd of people that aren’t necessarily tied to the task (e.g., all internet users can edit Wikipedia), but then people from the crowd either get chosen to participate, or volunteer themselves. When a crowd is providing financial contributions, that is called crowdfunding (e.g., patreon, kickstarter, gofundme). Humans have always collaborated on tasks, and crowds have been enlisted in performing tasks long before the internet existed. What social media (and other internet systems) have done is expand the options for how people can collaborate on tasks.

15.1.5. Volunteer Moderation# Letting individuals moderate their own spaces is expecting individuals to put in their own time and labor. You can do the same thing with larger groups and have volunteers moderate them. Reddit does something similar where subreddits are moderated by volunteers, and Wikipedia moderators (and editors) are also volunteers.

14.1. What Content Gets Moderated# Social media platforms moderate (that is ban, delete, or hide) different kinds of content. There are a number of categories that they might ban things: 14.1.1. Quality Control# In order to make social media sites usable and interesting to users, they may ban different types of content such as advertisements, disinformation, or off-topic posts. Almost all social media sites (even the ones that claim “free speech”) block spam, mass-produced unsolicited messages, generally advertisements, scams, or trolling. Without quality control moderation, the social media site will likely fill up with content that the target users of the site don’t want, and those users will leave. What content is considered “quality” content will vary by site, with 4chan considering a lot of offensive and trolling content to be “quality” but still banning spam (because it would make the site repetitive in a boring way), while most sites would ban some offensive content. 14.1.2. Legal Concerns# Social media sites also might run into legal concerns with allowing some content to be left up on their sites, such as copyrighted material (like movie clips) or child pornography. So most social media sites will often have rules about content moderation, and at least put on the appearance of trying to stop illegal content (though a few will try to move to countries that won’t get them in trouble, like 8kun is getting hosted in Russia). With copyrighted content, the platform YouTube is very aggressive in allowing movie studios to get videos taken down, so many content creators on YouTube have had their videos taken down erroneously. 14.1.3. Safety# Another concern is for the safety of the users on the social media platform (or at least the users that the platform cares about). Users who don’t feel safe will leave the platform, so social media companies are incentivized to help their users feel safe. So this often means moderation to stop trolling and harassment. 14.1.4. Potentially Offensive# Another category is content that users or advertisers might find offensive. If users see things that offend them too often, they might leave the site, and if advertisers see their ads next to too much offensive content, they might stop paying for ads on the site. So platforms might put limits on language (e.g., racial slurs), violence, sex, and nudity. Sometimes different users or advertisers have different opinions on what should be allowed or not. For example, “The porn ban of 2018 was a defining event for Tumblr that led to a 30 percent drop in traffic and a mass exodus of users that blindsided the company.”

13.4. Mental Health Detection# Since social media platforms can gather so much data on their users, they can try to use data mining to figure out information about their users’ moods, mental health problems, or neurotypes (e.g., ADHD, Autism). For example, Facebook has a suicide detection algorithm, where they try to intervene if they think a user is suicidal (Inside Facebook’s suicide algorithm: Here’s how the company uses artificial intelligence to predict your mental state from your posts). As social media companies have tried to detect talk of suicide and sometimes remove content that mentions it, users have found ways of getting around this by inventing new word uses, like “unalive.” Larger efforts at trying to determine emotions or mental health through things like social media use, or iPhone or iWatch use, have had very questionable results, and any claims of being able to detect emotions reliably are probably false. Additionally, these attempts at detecting mental health can be part of violating privacy or can be used for unethical surveillance, such as: your employer might detect that you are unhappy, and consider firing you since they think you might not be fully committed to the job someone might build a system that tries to detect who is Autistic, and then force them into an abusive therapy system to try and “cure” them of their Autism (see also this more scientific explanation of that linked article) { requestKernel: true, binderOptions: { repo: "binder-examples/jupyter-stacks-datascience", ref: "master", }, codeMirrorConfig: { theme: "abcdef", mode: "python" }, kernelOptions: { kernelName: "python3", path: "./ch13_mental_health" }, predefinedOutput: true } kernelName = 'python3'

13.2.1. Doomscrolling# Doomscrolling is: “Tendency to continue to surf or scroll through bad news, even though that news is saddening, disheartening, or depressing. Many people are finding themselves reading continuously bad news about COVID-19 without the ability to stop or step back.” Merriam-Webster Dictionary Fig. 13.1 Tweet on doomscrolling the day after insurrectionists stormed the US Capital (while still in the middle of the COVID pandemic).# The seeking out of bad news, or trying to get news even though it might be bad, has existed as long as people have kept watch to see if a family member will return home safely. But of course, new mediums can provide more information to sift through and more quickly, such as with the advent of the 24-hour news cycle in the 1990s, or, now social media. 13.2.2. Trauma Dumping# While there are healthy ways of sharing difficult emotions and experiences (see the next section), when these difficult emotions and experiences are thrown at unsuspecting and unwilling audiences, that is called trauma dumping. Social media can make trauma dumping easier. For example, with parasocial relationships, you might feel like the celebrity is your friend who wants to hear your trauma. And with context collapse, where audiences are combined, how would you share your trauma with an appropriate audience and not an inappropriate one (e.g., if you re-post something and talk about how it reminds you of your trauma, are you dumping it on the original poster?). Trauma dumping can be bad for the mental health of those who have this trauma unexpectedly thrown at them, and it also often isn’t helpful for the person doing the trauma dumping either: Venting, by contrast, is a healthy form of expressing negative emotion, such as anger and frustration, in order to move past it and find solutions. Venting is done with the permission of the listener and is a one-shot deal, not a recurring retelling or rumination of negativity. A good vent allows the venter to get a new perspective and relieve pent-up stress and emotion. While there are benefits to venting, there are no benefits to trauma dumping. In trauma dumping, the person oversharing doesn’t take responsibility or show self-reflection. Trauma dumping is delivered on the unsuspecting. The purpose is to generate sympathy and attention not to process negative emotion. The dumper doesn’t want to overcome their trauma; if they did, they would be deprived of the ability to trauma dump. How to Overcome Social Media Trauma Dumping

12.4. Virality and Intention# When someone creates content that goes viral, they didn’t necessarily intend it to go viral, or viral in the way that it does. If a user posts a joke, and people share it because they think it is funny, then their intention and the way the content goes viral is at least somewhat aligned. If a user tries to say something serious, but it goes viral for being funny, then their intention and the virality are not aligned. Let’s look at some examples of the relationship between virality and intent. 12.4.1. Building on the original intention# Content is sometimes shared without modification fitting the original intention, but let’s look at ones where there is some sort of modification that aligns with the original intention. We’ll include several examples on this page from the TikTok Duet feature, which allows people to build off the original video by recording a video of themselves to play at the same time next to the original. So for example, This tweet thread of TikTok videos (cross-posted to Twitter) starts with one Tiktok user singing a short parody musical of an argument in a grocery store. The subsequent tweets in the thread build on the prior versions, first where someone adds themselves singing the other half of the argument, then where someone adds themselves singing the part of their child, then where someone adds themselves singing the part of an employee working at the store1:

12.1.2. Memes# In the 1976 book The Selfish Gene, evolutionary biologist Richard Dawkins1 said rather than looking at the evolution of organisms, it made even more sense to look at the evolution of the genes of those organisms (sections of DNA that perform some functions and are inherited). For example, if a bee protects its nest by stinging an attacking animal and dying, then it can’t reproduce and it might look like a failure of evolution. But if the gene that told the bee to die protecting the nest was shared by the other bees in the nest, then that one bee dying allows the gene to keep being replicated, so the gene is successful evolutionarily. Since genes contained information about how organisms would grow and live, then biological evolution could be considered to be evolving information. Dawkins then took this idea of the evolution of information and applied it to culture, coining the term “meme” (intended to sound like “gene”). A meme is a piece of culture that might reproduce in an evolutionary fashion, like a hummable tune that someone hears and starts humming to themselves, perhaps changing it, and then others overhearing next. In this view, any piece of human culture can be considered a meme that is spreading (or failing to spread) according to evolutionary forces. So we can use an evolutionary perspective to consider the spread of: Technology (languages, weapons, medicine, writing, math, computers, etc.), religions philosophies political ideas (democracy, authoritarianism, etc.) art organizations etc. We can even consider the evolutionary forces that play in the spread of true and false information (like an old saying: “A lie is halfway around the world before the truth has got its boots on.”)

11.4.1. Filter Bubbles# One concern with how recommendation algorithms is that they can create filter bubbles (or “epistemic bubbles” or “echo chambers”), where people get filtered into groups and the recommendation algorithm only gives people content that reinforces and doesn’t challenge their interests or beliefs. These echo chambers allow people in the groups to freely have conversations among themselves without external challenge. The filter bubbles can be good or bad, such as forming bubbles for: Hate groups, where people’s hate and fear of others gets reinforced and never challenged Fan communities, where people’s appreciation of an artist, work of art, or something is assumed, and then reinforced and never challenged Marginalized communities can find safe spaces where they aren’t constantly challenged or harassed (e.g., a safe space)

When social media platforms show users a series of posts, updates, friend suggestions, ads, or anything really, they have to use some method of determining which things to show users. The method of determining what is shown to users is called a recommendation algorithm, which is an algorithm (a series of steps or rules, such as in a computer program) that recommends posts for users to see, people for users to follow, ads for users to view, or reminders for users. Some recommendation algorithms can be simple such as reverse chronological order, meaning it shows users the latest posts (like how blogs work, or Twitter’s “See latest tweets” option). They can also be very complicated taking into account many factors, such as: Time since posting (e.g., show newer posts, or remind me of posts that were made 5 years ago today) Whether the post was made or liked by my friends or people I’m following How much this post has been liked, interacted with, or hovered over Which other posts I’ve been liking, interacting with, or hovering over What people connected to me or similar to me have been liking, interacting with, or hovering over What people near you have been liking, interacting with, or hovering over (they can find your approximate location, like your city, from your internet IP address, and they may know even more precisely) This perhaps explains why sometimes when you talk about something out loud it gets recommended to you (because someone around you then searched for it). Or maybe they are actually recording what you are saying and recommending based on that. Phone numbers or email addresses (sometimes collected deceptively) can be used to suggest friends or contacts. And probably many more factors as well!

10.3. Why It Matters Who Designs# 10.3.1. Who gets designed for# When designers and programmers don’t think to take into account different groups of people, then they might make designs that don’t work for everyone. This problem often shows up in how designs do or do not work for people with disabilities. But it also shows up in other areas as well.

A disability is an ability that a person doesn’t have, but that their society expects them to have.1 For example: If a building only has staircases to get up to the second floor (it was built assuming everyone could walk up stairs), then someone who cannot get up stairs has a disability in that situation. If a physical picture book was made with the assumption that people would be able to see the pictures, then someone who cannot see has a disability in that situation. If tall grocery store shelves were made with the assumption that people would be able to reach them, then people who are short, or who can’t lift their arms up, or who can’t stand up, all would have a disability in that situation. If an airplane seat was designed with little leg room, assuming people’s legs wouldn’t be too long, then someone who is very tall, or who has difficulty bending their legs would have a disability in that situation. Which abilities are expected of people, and therefore what things are considered disabilities, are socially defined. Different societies and groups of people make different assumptions about what people can do, and so what is considered a disability in one group, might just be “normal” in another.

But while that is the proper security for storing passwords. So for example, Facebook stored millions of Instagram passwords in plain text, meaning the passwords weren’t encrypted and anyone with access to the database could simply read everyone’s passwords. And Adobe encrypted their passwords improperly and then hackers leaked their password database of 153 million users. From a security perspective there are many risks that a company faces, such as: Employees at the company misusing their access, like Facebook employees using their database permissions to stalk women Hackers finding a vulnerability and inserting, modifying, or downloading information. For example: hackers stealing the names, Social Security numbers, and birthdates of 143 million Americans from Equifax hackers posting publicly the phone numbers, names, locations, and some email addresses of 530 million Facebook users, or about 7% of all people on Earth

There are many reasons, both good and bad, that we might want to keep information private. There might be some things that we just feel like aren’t for public sharing (like how most people wear clothes in public, hiding portions of their bodies) We might want to discuss something privately, avoiding embarrassment that might happen if it were shared publicly We might want a conversation or action that happens in one context not to be shared in another (context collapse) We might want to avoid the consequences of something we’ve done (whether ethically good or bad), so we keep the action or our identity private We might have done or said something we want to be forgotten or make at least made less prominent We might want to prevent people from stealing our identities or accounts, so we keep information (like passwords) private We might want to avoid physical danger from a stalker, so we might keep our location private We might not want to be surveilled by a company or government that could use our actions or words against us (whether what we did was ethically good or bad) When we use social media platforms though, we at least partially give up some of our privacy.

8.7. Data Poisoning# People working with data sets always have to deal with problems in their data, stemming from things like mistyped data entries, missing data, and the general problem of all data being a simplification of reality. Sometimes a dataset has so many problems that it is effectively poisoned or not feasible to work with. 8.7.1. Unintentional Data Poisoning# Datasets can be poisoned unintentionally. For example, many scientists posted online surveys that people can get paid to take. Getting useful results depended on a wide range of people taking them. But when one TikToker’s video about taking them went viral, the surveys got filled out with mostly one narrow demographic, preventing many of the datasets from being used as intended. See more in A teenager on TikTok disrupted thousands of scientific studies with a single video – The Verge

Some data is directly provided to the platform by the users. Platforms may ask users for information like: email address name profile picture interests friends Platforms also collect information on how users interact with the site. They might collect information like (they don’t necessarily collect all this, but they might): when users are logged on and logged off who users interact with What users click on what posts users pause over where users are located what users send in direct messages to each other Online advertisers can see what pages their ads are being requested on, and track users across those sites. So, if an advertiser sees their ad is being displayed on an Amazon page for shoes, then the advertiser can start showing shoe ads to that same user when they go to another website.

We can trace Internet trolling to early social media in the 1980s and 1990s, particularly in early online message boards and in early online video games. In the early Internet message boards that were centered around different subjects, experienced users would “troll for newbies” by posting naive questions that all the experienced users were already familiar with. The “newbies” who didn’t realize this was a troll would try to engage and answer, and experienced users would feel superior and more part of the group knowing they didn’t fall for the troll like the “newbies” did. These message boards are where the word “troll” with this meaning comes from.

Trolling is when an Internet user posts inauthentically (often false, upsetting, or strange) with the goal of causing disruption or provoking an emotional reaction. When the goal is provoking an emotional reaction, it is often for a negative emotion, such as anger or emotional pain. When the goal is disruption, it might be attempting to derail a conversation (e.g., concern trolling), or make a space no longer useful for its original purpose (e.g., joke product reviews), or try to get people to take absurd fake stories seriously.

Arizona State University confirmed that they had no professors who matched the description of @Sciencing_Bi. Dr. McLaughlin’s and @Sciencing_Bi’s accounts were suspended from Twitter for violating Twitter policies, and Dr. McLaughlin eventually confirmed that she had completely invented @Sciencing_Bi.

“What’s more, we can see that the Android tweets are angrier and more negative, while the iPhone tweets tend to be benign announcements and pictures. …. this lets us tell the difference between the campaign’s tweets (iPhone) and Trump’s own (Android).”

The comedy website Something Awful was created in 1999, and it included web forums where many popular memes of the day originated. While the Something Awful forums had edgy content, one 15-year-old member of the Something Awful forum called “Anime Death Tentacle Rape Whorehouse” was frustrated by content restrictions on Something Awful, and created his own new site with less restrictions: 4Chan. 5.5.2. 4Chan# 4Chan was created in 2003 by copying the code from a Japanese image-sharing bulletin board called Futaba or 2chan.

Graffiti and other notes left on walls were used for sharing updates, spreading rumors, and tracking accounts Books and news write-ups had to be copied by hand, so that only the most desired books went “viral” and spread

Data points often give the appearance of being concrete and reliable, especially if they are numerical. So when Twitter initially came out with a claim that less than 5% of users are spam bots, it may have been accepted by most people who heard it. Elon Musk then questioned that figure and attempted to back out of buying Twitter, and Twitter is accusing Musk’s complaint of being an invented excuse to back out of the deal, and the case is now in court.

Metadata is information about some data. So we often think about a dataset as consisting of the main pieces of data (whatever those are in a specific situation), and whatever other information we have about that data (metadata).

[Morten] Bay found that 50.9% of people tweeting negatively about “The Last Jedi” were “politically motivated or not even human,” with a number of these users appearing to be Russian trolls. The overall backlash against the film wasn’t even that great, with only 21.9% of tweets analyzed about the movie being negative in the first place.

Bots present a similar disconnect between intentions and actions. Bot programs are written by one or more people, potentially all with different intentions, and they are run by others people, or sometimes scheduled by people to be run by computers.

“Rational Selfishness”: It is rational to seek your own self-interest above all else. Great feats of engineering happen when brilliant people ruthlessly follow their ambition.

“We’re not making it for that reason but the way ppl choose to use it isn’t our fault. Safeguard will develop.” But tech is moving so fast. That there is no way humanity or laws can keep up. We don’t even know how to deal with open death threats online.