As you do this you might consider personality differences (such as introverts and extroverts), and neurodiversity, the ways people’s brains work and process information differently (e.g., ADHD, Autism, Dyslexia, Face blindness, depression, anxiety). But be careful generalizing about different neurotypes (such as Autism), especially if you don’t know them well. Instead try to focus on specific traits (that may or may not be part of a specific group) and the impacts on them (e.g., someone easily distracted by motion might…., or someone sensitive to loud sounds might…, or someone already feeling anxious might…).

Many have anecdotal experiences with their own mental health and those they talk to. For example, cosmetic surgeons have seen how photo manipulation on social media has influenced people’s views of their appearance:

To use loop variables, we create a variable before our loop, and give it an initial value (often 0). Then within the loop over each item in our list, we can optionally add something to our loop variable. After the loop, our variable will have our final result.

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.

What assumptions do the site and your device make about individuals or groups using social media, which might not be true or might cause problems? List as many as you can think of (bullet points encouraged).

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.

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, a social media application might offer us a way of “Private Messaging” (also called Direct Messaging) with another user. But in most cases those “private” messages are stored in the computers at those companies, and the company might have computer programs that automatically search through the messages, and people with the right permissions might be able to view them directly.

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.

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.

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.

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.

Every “we” implies a not-“we”. A group is constituted in part by who it excludes. Think back to the origin of humans caring about authenticity: if being able to trust each other is so important, then we need to know WHICH people are supposed to be entangled in those bonds of mutual trust with us, and which are not from our own crew. As we have developed larger and larger societies, states, and worldwide communities, the task of knowing whom to trust has become increasingly large. All groups have variations within them, and some variations are seen as normal. But the bigger groups get, the more variety shows up, and starts to feel palpable. In a nation or community where you don’t know every single person, how do you decide who’s in your squad?

Trolling is when an Internet user posts inauthentically (often false, upsetting, or strange) with the goal of causing disruption or provoking an emotional reaction.

Authenticity is a concept we use to talk about connections and interactions when the way the connection is presented matches the reality of how it functions. An authentic connection can be trusted because we know where we stand. An inauthentic connection offers a surprise because what is offered is not what we get. An inauthentic connection could be a good surprise, but usually, when people use the term ‘inauthentic’, they are indicating that the surprise was in some way problematic: someone was duped.

This is not to say that there is no room for appreciating connections that are not fully honest, transparent, and earnest all the time. Social media spaces have allowed humor and playfulness to flourish, and sometimes humor and play are not, strictly speaking, honest. Often, this does not bother us, because the kind of connection offered by joke accounts matches the jokey way they interact on social media. We get to know a lot about public figures and celebrities, but it is not usually considered problematic for celebrity social media accounts to be run by publicist teams. As long as we know where we stand, and the kind of connection being offered roughly matches the sort of connection we’re getting, things go okay.

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.

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.

In our example tweet we can see several places where data could be saved in lists:

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. Now that we’ve looked some at the data in a tweet, let’s look next at how different pieces of this information are saved.

We also would like to point out that there are fake bots as well, that is real people pretending their work is the result of a Bot. For example, TikTok user Curt Skelton posted a video claiming that he was actually an AI-generated / deepfake character:

As one example, in 2016, Rian Johnson, who was in the middle of directing Star Wars: The Last Jedi, got bombarded by tweets that all originated in Russia (likely making at least some use of bots).