We covered a number of topics in relation to social media: Bots Data History of Social Media Authenticity Trolling Data Mining Privacy and Security Accessibility Recommendation Algorithms Virality Mental Health Content Moderation Content Moderators Crowdsourcing Harassment Public Shaming Capitalism Colonialism We hope that by the end of this book you know a lot of social media terminology (e.g., context collapse, parasocial relationships, the network effect, etc.), that you have a good overview of how social media works and is used, and what design decisions are made in how social media works, and the consequences of those decisions. We also hope you are able to recognize how trends on internet-based social media tie to the whole of human history of being social and can apply lessons from that history to our current situations.

As a social media user, we hope you are informed about things like: how social media works, how they influence your emotions and mental state, how your data gets used or abused, strategies in how people use social media, and how harassment and spam bots operate. We hope with this you can be a more informed user of social media, better able to participate, protect yourself, and make it a valuable experience for you and others you interact with. For example, you can hopefully recognize when someone is intentionally posting something bad or offensive (like the bad cooking videos we mentioned in the Virality chapter, or an intentionally offensive statement) in an attempt to get people to respond and spread their content. Then you can decide how you want to engage (if at all) given how they are trying to spread their content.

Reflect on these prompts and try to work out what the consequences would be for different ways of social media working: What if social media sites were governed by their users instead of by shareholders (e.g., governed by the subjugated instead of the colonialists)? How would users participate in decision-making? Would non-users have a say (e.g., if the whole user base decides to harass a group of non-users)? How do you think the sites would work differently? What if social media sites were created in other countries and cultures? (Note: we already have various Chinese social media sites as one point of comparison) What different values would be embedded and what would that look like? For example, many cultures value family connections much more than white Americans do, but current American social media sites do not emphasize them.

The tech industry is full of colonialist thinking and practices, some more subtle than others. To begin with, much of the tech industry is centralized geographically, specifically in Silicon Valley, San Francisco, California. The leaders and decisions in how tech operates come out of this one wealthy location in a wealthy nation. Then, much of tech is dependent on exploiting cheap labor, often in dangerous conditions, in other countries (thus extracting the resource of cheap labor, from places with “inferior” governments and economies). This labor might be physical labor, or dealing with dangerous chemicals, or the content moderators who deal with viewing horrific online content. Tech industry leaders in Silicon Valley then take what they made with exploited labor, and sell it around the world, feeling good about themselves, believing they are benefitting the world with their “superior” products.

When Facebook started, there were already other social media platforms in use that Facebook had to compete against, but Facebook became dominant. Since then other companies have tried to compete with Facebook, with different levels of success. Google+ tried to mimic much of what Facebook did, but it got little use and never took off (not enough people to benefit from the network effect). Other social media sites have used more unique features to distinguish themselves from Facebook and get a foothold, such as Twitter with its character limit (forcing short messages, so you can see lots of posts in quick succession), Vine and then TikTok based on short videos, etc. Mastodon (Fediverse set of connected social media platforms that it is part of) has a different way of distinguishing itself as a social media network, in that it is an open-source, community-funded social media network (no ads), and hopes people will join to get away from corporate control. Other social media networks have focused on parts of the world where Facebook was less dominant, and so they got a foothold there first, and then spread, like the social media platforms in China (e.g., Sina Weibo, QQ, and TikTok).

19.2.2. Meta’s Business Model# So, what Meta does to make money (that is, how shareholders get profits), is that they collect data on their users to make predictions about them (e.g., demographics, interests, etc.). Then they sell advertisements, giving advertisers a large list of categories that they can target for their ads. The way that Meta can fulfill their fiduciary duty in maximizing profits is to try to get: More users: If Meta has more users, it can offer advertisers more people to advertise to. More user time: If Meta’s users spend more time on Meta, then it has more opportunities to show ads to each user, so it can sell more ads. More personal data: The more personal data Meta collects, the more predictions about users it can make. It can get more data by getting more users, and more user time, as well as finding more things to track about users. Reduce competition: If Meta can become the only social media company that people use, then they will have cornered the market on access to those users. This means advertisers won’t have any alternative to reach those users, and Meta can increase the prices of their ads.

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).

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.

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

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.

Some online platforms are specifically created for crowdsourcing. For example: Wikipedia: Is an online encyclopedia whose content is crowdsourced. Anyone can contribute, just go to an unlocked Wikipedia page and press the edit button. Institutions don’t get special permissions (e.g., it was a scandal when US congressional staff edited Wikipedia pages), and the expectation that editors do not have outside institutional support is intended to encourage more people to contribute. Quora: An crowdsourced question and answer site. Stack Overflow: A crowdsourced question-and-answer site specifically for programming questions. Amazon Mechanical Turk: A site where you can pay for crowdsourcing small tasks (e.g., pay a small amount for each task, and then let a crowd of people choose to do the tasks and get paid). Upwork: A site that lets people find and contract work with freelancers (generally larger and more specialized tasks than Amazon Mechanical Turk. Project Sidewalk: Crowdsourcing sidewalk information for mobility needs (e.g., wheelchair users).

There have been many efforts to use computers to replicate the experience of communicating with someone in person, through things like video chats, or even telepresence robots]. But there are ways that attempts to recreate in-person interactions inevitably fall short and don’t feel the same. Instead though, we can look at different characteristics that computer systems can provide, and find places where computer-based communication works better, and is Beyond Being There (pdf here). Some of the different characteristics that means of communication can have include (but are not limited to): Location: Some forms of communication require you to be physically close, some allow you to be located anywhere with an internet signal. Time delay: Some forms of communication are almost instantaneous, some have small delays (you might see this on a video chat system), or have significant delays (like shipping a package). Synchronicity: Some forms of communication require both participants to communicate at the same time (e.g., video chat), while others allow the person to respond when convenient (like a mailed physical letter). Archiving: Some forms of communication automatically produce an archive of the communication (like a chat message history), while others do not (like an in-person conversation) Anonymity: Some forms of communication make anonymity nearly impossible (like an in-person conversation), while others make it easy to remain anonymous. -Audience: Communication could be private or public, and they could be one-way (no ability to reply), or two+-way where others can respond.

Some people view internet-based social media (and other online activities) as inherently toxic and therefore encourage a digital detox, where people take some form of a break from social media platforms and digital devices. While taking a break from parts or all of social media can be good for someone’s mental health (e.g., doomscrolling is making them feel more anxious, or they are currently getting harassed online), viewing internet-based social media as inherently toxic and trying to return to an idyllic time from before the Internet is not a realistic or honest view of the matter. In her essay “The Great Offline,” Lauren Collee argues that this is just a repeat of earlier views of city living and the “wilderness.” As white Americans were colonizing the American continent, they began idealizing “wilderness” as being uninhabited land (ignoring the Indigenous people who already lived there, or kicking them out or killing them).

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)

For social media content, replication means that the content (or a copy or modified version) gets seen by more people. Additionally, when a modified version gets distributed, future replications of that version will include the modification (a.k.a., inheritance). There are ways of duplicating that are built into social media platforms: Actions such as: liking, reposting, replying, and paid promotion get the original posting to show up for users more Actions like quote tweeting, or the TikTok Duet feature let people see the original content, but modified with new context. Social media sites also provide ways of embedding posts in other places, like in news articles There are also ways of replicating social media content that aren’t directly built into the social media platform, such as: copying images or text and reposting them yourself taking screenshots, and cross-posting to different sites

Biological evolution is how living things change, generation after generation, and how all the different forms of life, from humans to bacteria, came to be. Evolution occurs when three conditions are present: Replication (with Inheritance) An organism can make a new copy of itself, which inherits its characteristics Variations / Mutations The characteristics of an organism are sometimes changed, in a way that can be inherited by future copies Natural Selection Some characteristics make it more or less likely for an organism to compete for resources, survive, and make copies of itself

Knowing that there is a recommendation algorithm, users of the platform will try to do things to make the recommendation algorithm amplify their content. This is particularly important for people who make their money from social media content. For example, in the case of the simple “show latest posts” algorithm, the best way to get your content seen is to constantly post and repost your content (though if you annoy users too much, it might backfire). Other strategies include things like: Clickbait: trying to give you a mystery you have to click to find the answer to (e.g., “You won’t believe what happened when this person tried to eat a stapler!”). They do this to boost clicks on their link, which they hope boosts them in the recommendation algorithm, and gets their ads more views Trolling: by provoking reactions, they hope to boost their content more Coordinated actions: have many accounts (possibly including bots) like a post, or many people use a hashtag, or have people trade positive reviews

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!

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!

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!

Another way of managing disabilities is assistive technology, which is something that helps a disabled person act as though they were not disabled. In other words, it is something that helps a disabled person become more “normal” (according to whatever a society’s assumptions are). For example: Glasses help people with near-sightedness see in the same way that people with “normal” vision do Walkers and wheelchairs can help some disabled people move around closer to the way “normal” people can (though stairs can still be a problem) A spoon might automatically balance itself when held by someone whose hands shake Stimulants (e.g., caffeine, Adderall) can increase executive function in people with ADHD, so they can plan and complete tasks more like how neurotypical people do.

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.

While we have our concerns about the privacy of our information, we often share it with social media platforms under the understanding that they will hold that information securely. But social media companies often fail at keeping our information secure. For example, the proper security practice for storing user passwords is to use a special individual encryption process for each individual password. This way the database can only confirm that a password was the right one, but it can’t independently look up what the password is or even tell if two people used the same password. Therefore if someone had access to the database, the only way to figure out the right password is to use “brute force,” that is, keep guessing passwords until they guess the right one (and each guess takes a lot of time). 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.

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)

Social Media platforms use the data they collect on users and infer about users to increase their power and increase their profits. One of the main goals of social media sites is to increase the time users are spending on their social media sites. The more time users spend, the more money the site can get from ads, and also the more power and influence those social media sites have over those users. So social media sites use the data they collect to try and figure out what keeps people using their site, and what can they do to convince those users they need to open it again later. Social media sites then make their money by selling targeted advertising, meaning selling ads to specific groups of people with specific interests. So, for example, if you are selling spider stuffed animal toys, most people might not be interested, but if you could find the people who want those toys and only show your ads to them, your advertising campaign might be successful, and those users might be happy to find out about your stuffed animal toys. But targeting advertising can be used in less ethical ways, such as targeting gambling ads at children, or at users who are addicted to gambling, or the 2016 Trump campaign ‘target[ing] 3.5m black Americans to deter them from voting’

When we’ve been accessing Reddit through Python and the “PRAW” code library. The praw code library works by sending requests across the internet to Reddit, using what is called an “application programming interface” or API for short. APIs have a set of rules for what requests you can make, what happens when you make the request, and what information you can get back. If you are interested in learning more about what you can do with praw and what information you can get back, you can look at the official documentation for those. But be warned they are not organized in a friendly way for newcomers and take some getting used to to figure out what these documentation pages are talking about. So, if you are interested, you can look at the praw library documentation to find out what the library can do (again, not organized in a beginner-friendly way). You can learn a little more by clicking on the praw models and finding a list of the types of data for each of the models, and a list of functions (i.e., actions) you can do with them.

If the immediate goal of the action of trolling is to cause disruption or provoke emotional reactions, what is it that makes people want to do this disruption or provoking of emotional reactions? Some reasons people engage in trolling behavior include: Amusement: Trolls often find the posts amusing, whether due to the disruption or emotional reaction. If the motivation is amusement at causing others’ pain, that is called doing it for the lulz. Gatekeeping: Some trolling is done in a community to separate out an ingroup from outgroup (sometimes called newbies or normies). The ingroup knows that a post is just trolling, but the outgroup is not aware and will engage earnestly. This is sometimes known as trolling the newbies. Feeling Smart: Going with the gatekeeping role above, trolling can make a troll or observer feel smarter than others, since they are able to see that it is trolling while others don’t realize it. Feeling Powerful: Trolling sometimes gives trolls a feeling of empowerment when they successfully cause disruption or cause pain.** Advance and argument / make a point: Trolling is sometimes done in order to advance an argument or make a point. For example, proving that supposedly reliable news sources are gullible by getting them to repeat an absurd gross story. Punish or stop: Some trolling is in service of some view of justice, where a person, group or organization is viewed as doing something “bad” or “deserving” of punishment, and trolling is a way of fighting back.

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

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.

In 2016, when Donald Trump was running a campaign to be the US President, one twitter user pointed out that you could see which of the Tweets on Donald Trump’s Twitter account were posted from an Android phone and which from an iPhone, and that the tone was very different. A data scientist decided to look into it more and found: “My analysis … concludes that the Android and iPhone tweets are clearly from different people, “posting during different times of day and using hashtags, links, and retweets in distinct ways, “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).” (Read more in this article from The Guardian) Note: we can no longer run code to check this ourselves because first, Donald Trump’s account was suspended in January 2021 for inciting violence, then when Elon Musk decided to reinstate Donald Trump’s account (using a Twitter poll as an excuse, but how many of the votes were bots?), Elon Musk also decided to remove the ability to look up a tweet’s source.

As we talked about previously in a section of Chapter 2 (What is Social Media?), pretty much anything can count as social media, and the things we will see in internet-based social media show up in many other places as well. The book Writing on the Wall: Social Media - The First 2,000 Years by Tom Standage outlines some of the history of social media before internet-based social media platforms such as in times before the printing press: 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 Later, sometime after the printing press, Stondage highlights how there was an unusual period in American history that roughly took up the 1900s where, in America, news sources were centralized in certain newspapers and then the big 3 TV networks. In this period of time, these sources were roughly in agreement and broadcast news out to the country, making a more unified, consistent news environment (though, of course, we can point out how they were biased in ways like being almost exclusively white men). Before this centralization of media in the 1900s, newspapers and pamphlets were full of rumors and conspiracy theories. And now as the internet and social media have taken off in the early 2000s, we are again in a world full of rumors and conspiracy theories.

In the first decade of the 2000s the way websites worked on the Internet went through a transition to what is called “Web 2.0.” In Web 2.0 websites (and web applications), the communication platforms and personal profiles merged. Many websites now let you create a profile, form connections, and participate in discussions with other members of the site. Platforms for hosting content without having to create your own website (like Blogs) emerged. And all of these websites became much more interactive, with updates appearing on users’ screens without the user having to request them.

The other method of grouping data that we will discuss here is called a “dictionary” (sometimes also called a “map”). You can think of this as like a language dictionary where there is a word and a definition for each word. Then you can look up any name or word and find the value or definition. Example: An English Language Dictionary with definitions of three terms: Social Media: An internet-based platform used for people to form connections to each other and share things. Ethics: Thinking systematically about what makes something morally right or wrong, or using ethical systems to analyze moral concerns in different situations Automation: Making a process or activity that can run on its own without needing a human to guide it.

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). For example: If we think of a tweet’s contents (text and photos) as the main data of a tweet, then additional information such as the user, time, and responses would be considered metadata. If we download information about a set of tweets (text, user, time, etc.) to analyze later, we might consider that set of information as the main data, and our metadata might be information about our download process, such as when we collected the tweet information, which search term we used to find it, etc.

Most social media platforms provide an official way to connect a bot to their platform (called an Application Programming Interface, or API). This lets the social media platform track these registered bots and provide certain capabilities and limits to the bots (like a rate limit on how often the bot can post). But when some people want to get around these limits, they can make bots that don’t use this official API, but instead, open the website or app and then have a program perform clicks and scrolls the way a human might. These are much harder for social media platforms to track, and they normally ban accounts doing this if they are able to figure out that is what is happening.

There are other ways of programming with social media that we won’t consider a bot (and we will cover these at various points as well): The social media platform itself is run with computer programs, such as recommendation algorithms (chapter 12). Various groups want to gather data from social media, such as advertisers and scientists. This data is gathered and analyzed with computer programs, which we will not consider bots, but will cover later, such as in Chapter 8: Data Mining.

Confucianism (another link)# Being and becoming an exemplary person (e.g., benevolent; sincere; honoring and sacrificing to ancestors; respectful to parents, elders and authorities, taking care of children and the young; generous to family and others). These traits are often performed and achieved through ceremonies and rituals (including sacrificing to ancestors, music, and tea drinking), resulting in a harmonious society. Key figures: Confucius ~500, China Mencius ~350, China Xunzi ~300 BCE, China

There are absolute moral rules and duties to follow (regardless of the consequences). They can be deduced by reasoning about the objective reality. Kantianism: “Act only according to that maxim whereby you can, at the same time, will that it should become a universal law.” Meaning: only follow rules that you are ok with everyone else following. For example, you might conclude that it is wrong to lie no matter what the consequences are. Kant certainly thought so, but many have disagreed with him. Deontological thinking comes out of the same era as Natural Rights thinking, and they are rooted in similar assumptions about the world. Deontology is often associated with Kant, because at that time, he gave us one of the first systematic, or comprehensive, interpretations of those ideas in a fully-fledged ethical framework. But deontological ethics does not need to be based on Kant’s ethics, and many ethicists working in the deontological tradition have suggested that reasoning about the objective reality should lead us to derive different sets of principles. Key figures: Immanuel Kant, 1700’s Germany Christine Korsgaard present USA