I chose this source because it shows that copyright moderation can go wrong on a very large scale. If so many claims were later overturned, that suggests legal moderation is not always accurate, even on a platform as big as YouTube. That connects well to this chapter’s point that moderation is often shaped by legal pressure, but the results are not always fair.

I thought this part was interesting because it shows that moderation is not only about ethics or safety, but also about making a platform usable at all. A lot of arguments about moderation focus on free speech, but this section reminds me that if everything is allowed, the site can become full of spam, scams, or repetitive content and stop being useful to regular users. That makes moderation feel less like an extra feature and more like part of what makes a platform function in the first place.

I picked this source because it pushes back against the simple idea that going “offline” is automatically the solution to problems caused by social media. I thought that was interesting because it makes the issue feel more complicated and more realistic. Instead of treating the internet as something that is just bad and needs to be escaped, this source suggests that we should think more about how online spaces are designed and how they could be improved.

I like this point because discussions about social media and mental health often become too simple too quickly. People sometimes talk as if social media is either obviously ruining people’s lives or obviously helping them stay connected, but this chapter points out that the reality is more mixed than that. I think that is important, because different platforms, different uses, and different people can have very different experiences. This also makes me think that the better question is not whether social media is “good” or “bad” overall, but what kinds of design and habits make it more harmful or more helpful.

I picked this source because it helped me understand that the original meaning of “meme” is much broader than how we usually use the word online. Now people mostly think of funny images or jokes, but the source shows that a meme can mean a cultural idea that gets copied and passed along. I think that makes this chapter more interesting, because it connects internet culture to a much bigger idea about how information spreads.

I liked this section because it made me think about memes in a much bigger way. Usually I only think of memes as internet jokes, but here they are more like ideas that spread and change over time. That also helps explain why false information can spread so easily online.

I chose this source because it makes invisible disability easier to understand. ME/CFS can seriously affect a person even if other people cannot see it, and symptoms can change over time. That connects well to the chapter’s point that not all disabilities are obvious from the outside.

I liked this definition because it makes disability feel less like a personal defect and more like a mismatch between people and the way society is designed. That stood out to me because it shifts the focus from “what is wrong with this person” to “what assumptions are built into this space or system.”

I thought this source was interesting because the “right to be forgotten” shows that privacy is not just about secrets. It is also about whether people can move on from old information that stays online for a long time. That connects well to this chapter’s point that privacy matters for many different reasons.

I thought this part was interesting because “private” messages on social media are not really fully private. They are private from other users, but not necessarily from the company. That feels important because a lot of people probably do not think about that difference very much when they use these apps.

This source says websites track what users do online and use it to understand behavior. I didn’t realize it includes things like what you click or watch. It feels a bit uncomfortable because it means a lot of personal info is being collected without we really noticing.

I agree with this part. A lot of AI writing sounds correct at first, but sometimes it is empty or wrong, and that can really lower the quality of a website.

I like this definition because it shows trolling is more than just being rude online. The main thing is that the person is trying to mess up the conversation or get a reaction out of people. I think that makes it different from normal disagreement, even if both can look offensive sometimes.

I thought this source was interesting because it shows trolling is not always just for fun or to make people mad. Sometimes it is also used to prove a point, especially by showing how easily people believe weird stories online. That connects well to this chapter.

This source seems especially relevant to the chapter because it shows how anonymity online can become ethically complicated very quickly. From the title alone, it already suggests a gap between the identity a person presented online and who they really were. That connects directly to this chapter’s discussion of how anonymity can support either authentic self-expression or harmful inauthentic behavior. Soufflé. What interests me most is that anonymity is not just about privacy — it can also affect trust, credibility, and harm when other people believe the identity being performed is real.

I think this part is really interesting because people often talk about anonymity as if it is automatically harmful, but this section shows that it can also help people express their real selves. Soufflé. In my opinion, anonymity is not good or bad by itself. It depends on the situation and on what kind of behavior it makes possible. For some people, especially those who fear judgment, punishment, or discrimination, anonymity can create space for honest self-expression that would be difficult in everyday life. That makes me think the ethical question is less about anonymity itself and more about what kinds of actions and communities anonymity supports.

I found this source interesting because bulletin board systems feel like an early version of features that are still common today, especially threads and community discussion spaces. Even though the technology was much simpler, the basic social pattern is familiar: one person posts, others reply, and a conversation forms around shared interests. This source made me realize that many features we associate with modern social media actually have much older roots.

I found this part interesting because it shows that the design of a platform affects how people interact. When personal webpages and communication tools were separate, online social life seems like it was more divided and maybe more intentional. Today, many platforms put everything together in one space, which makes interaction easier, but also creates more pressure to always be visible and active.

This source caught my attention because the title is surprising, but it makes an important point. I think the article helps show that numbers are not always as simple or objective as they first appear. In real-world situations, the meaning of a number often depends on definitions, assumptions, and context. That connects strongly to this chapter, especially the discussion of how measuring Twitter bots depends on how people define what they are counting.

The sentence “all data is a simplification of reality” really stood out to me. I like this point because it reminds us that data is never just a perfect copy of the real world. The apple example was simple, but it clearly showed that counting something as “one” can hide important differences. I think this also connects strongly to the Twitter bot example, because the result depends a lot on how people define words like “user” or “spam bot.” This made me realize that when we look at data, we should not only ask whether it is correct, but also ask what has been simplified or left out.

This source caught my attention because the title already suggests that bias in bots is a real design problem, not just a technical mistake. It connects to the chapter by reminding us that even simple program structures can still produce harmful outcomes if the data, rules, or assumptions behind them are biased.

This part made me think about how simple scheduling can make a bot feel much more active and intentional, even when it is doing a very basic task. A bot that posts at regular times may look more “human” or organized, which also raises ethical questions about transparency and whether other users should know they are interacting with automation.

I was most interested in the part saying ethics frameworks do not guarantee moral goodness. I agree because people can use the same framework to defend very different actions. This reminded me that ethical thinking in technology is not just about picking one theory, but about staying critical, comparing perspectives, and asking who might be harmed by a decision.

I want to add to ethics of care. The reading says it focuses on responsibilities in relationships, but I think it is also useful for social media because it highlights emotional harm that rule-based frameworks may miss. For example, even if a platform follows the same rule for everyone, it may still fail vulnerable users who need more protection and support.