I took a look at i4 about the right to privacy and how it protects people from government and company interference with their personal information. One thing that stood out to me was how privacy laws differ so much around the world, especially with countries like the European Union having stronger protections through GDPR compared to the US. I also found it interesting how technology and social media have made privacy more complicated because companies can collect big amounts of personal data online. Reading about "mass surveillance" and data collection made me realize how important privacy rights are now that so many things are digital and how difficult it can be to balance safety, security, and personal freedom.

I read i19 and one part of this article that stood out to me was the idea that employees often have an “illusion of privacy” when using workplace communication tools. I learned that many people assume private messages or deleted chats cant be seen, but companies can actually access emails, Slack messages, and even deleted content. This connects strongly to the topic of digital privacy because it shows how technology can blur the line between personal and professional communication. It also made me think about how important transparency is and why workers should clearly know what information employers can monitor and store.

One source from the bibliography that stood out to me was the Washington Post article h8 “Everything Everywhere All at Once is a deeply Asian American film.” The article explains how the multiverse in the movie represents the immigrant experience and the pressure of balancing different identities. I thought this was interesting because it shows that the movie is not only about action or science fiction, but also about family expectations, cultural identity, and generational trauma. The writer explains that Evelyn feels split between many versions of herself, which was meant to show how many immigrants or children of immigrants can feel caught between cultures. This detail helped me better understand why the film connected so strongly with audiences and why it is considered such an important movie for Asian American representation. This was a good read!

One thing I found interesting in this section was the idea of spurious correlations. Just because two things seem connected in data doesnt mean one actually causes the other. The example of comparing COVID cases and Yankee Candle reviews was funny but also showed how easy it is to misinterpret data online. I think this is important because social media companies and researchers use huge amounts of data to make decisions, so people need to think critically about whether the conclusions are actually reliable.

One thing that stood out to me in source m17 about cyberbullying, was how some teens anonymously cyberbully themselves online because they already feel insecure or alone. I thought it was really sad that some teenagers post hateful comments about themselves just to see if anyone notices or cares. This source shows how social media can sometimes make mental health struggles worse even from internal factors, especially for teens who already feel isolated. It also made me realize how important it is for parents, teachers, and friends to create supportive environments where teens feel safe talking about their feelings instead of suffering silently.

I thought this section was interesting because it showed how social media platforms could change what people see online by filtering posts with positive or negative sentiment. Even though only showing positive news might help some people feel better, I also think it could create an unrealistic view of the world if users never see important negative news. It made me think about how much control algorithms have over people’s emotions and perspectives online.

I took a look at the article about trolling slang and I thought it was interesting that this source explains how the meaning of “troll” has changed over time. Originally, trolling online was sometimes seen as more of an inside joke or prank, but now it is often connected to harassment and cyberbullying. I found it interesting about how its severity has taken on new levels as of more recently. I also found it surprising how the article connected trolling to psychology and online anonymity, because people often act differently online when they feel anonymous.

This example shows how easy it is for bots to be manipulated if they aren’t designed carefully. Even when the bot tried to limit actions, people still found ways to trick it into saying certain harmful things. It made me realize that technology isn’t automatically safe or neutral it depends a lot on how it’s programmed and how people choose to use it.

The f33 source talks about social media and anxiety and the NPR interview with Bo Burnham shows how social media can increase anxiety, especially for young people trying to figure out who they are. It connects well to the chapter because it highlights how hard it is to be “authentic” online when there is so much pressure to perform or be judged by others.

This part really showed me how serious inauthenticity online can be. The story about @Sciencing_Bi was surprising because so many people believed the account was real, and it actually affected real situations like harassment discussions. It made me realize how easy it is to trust what we see on social media without questioning it. Things like fake accounts or sockpuppets make it harder to know what’s true.

I looked at e9 about text messaging and it discussed the social effects of text messaging, especially among teenagers. Something that stood out to me was getting to look at both historical context and modern social impacts of texting. One detail that stood out was how texting has evolved from simple SMS messages into something that affects areas like education, law, and communication norms. The section about students showed how texting can impact academic performance and even lead to issues like cheating or reduced attention during classes. This source provides research based evidence that supports the idea that social media and messaging technologies influence behavior, not just communication.

I found it interesting how dictionaries organize data with keys and values, because it reminds me of how social media profiles have different types of information all in one place. It makes it easier to see how real apps use this structure

I took a look at d24, the article about bot activity on X during the Super Bowl, and it showed that around 75% of the traffic coming from the platform may have been fake. A detail from this source that stood out to me was how this was much higher compared to other platforms like Instagram or TikTok, which had very low percentages of fake traffic. This connects to what weve been learning about bots so far this course because it shows how they can significantly impact what we think is real engagement online.

This section made me think about how much information is actually contained and used in a single social media post, including both the content and the metadata like likes, time, and information about the user posting. This can be connected to my own experience using apps like Instagram and TikTok because I usually only pay attention to the post itself, not all the extra data behind it. I also didn’t realize how that hidden information could be used to understand or influence what people see what content.

I took a look at the “Programming paradigm” source from this bibliography section. This source helped me understand that programming isn’t just one way of writing code, but actually includes multiple “paradigms” that shape how problems are approached. What stood out to me is how coding languages like Python or Java can support more than one paradigm, which means there isn’t just one correct way to structure a program. This makes me think about how flexibility in programming reflects real world problem solving, where there is rarely just one way to solve an issue. The rest of the source basically explains different types of programming paradigms and how they classify and organize different programming languages.

This section helped me understand how bots are built using structured programming rules, similar to how language follows grammar rules to make sense. It made me realize that even something that seems simple or automatic online is actually the result of different, intentional design choices. This connects to the earlier parts of the reading about social media because it shows how much of what we see online is shaped by systems running in the background with these bots, not just human users.