This source gives an in-depth overview of the origin of the memes and how they have evolved. Specifically, I looked at how the word is defined. The word “meme” comes from the Ancient Greek word "mīmēma", which means “imitated thing.” Biologist Richard Dawkins coined the term in his book The Selfish Gene (1976). In the book, he used it to describe how ideas and culture spread the way genes do, using examples like catchphrases, melodies, and fashion. In a broader perspective, some memes spread because they provide simple explanations for why things are going wrong.

This is interesting that these chain letters existed because I remember when I was younger and people would send chain mail through text. This was a big deal to my friends and I, we would all be scared of the texts and send them to one another. I never thought about where this originated from, but it makes sense that it happened through mail and letters first. But to think that it started with people asking for money and that working is sort of crazy.

I decided to look into this source because in my INFO 200 class I researched Sasha Constanza-Chock and I recognized her name. This book talks a lot about what I mentioned in my previous Ch10 comment about marginalized groups and how systems are not built for them. This book Design Justice, discussed how design frequently leave out marginalized people because they are not considered a typical user and the design is not built with them in mind. The idea of letting marginalized groups lead the design process is the key to ensuring marginalized groups are heard and seen in designs.

It is interesting that as time goes on that things are still getting worse for disabled people because I feel like it should be getting better for disabled people. But, from a technology standpoint, I can understand that sometimes it is difficult to consider all groups of people when designing a product. In INFO 200, my class focused heavily on how negatively affected marginalized people are from technology because AI systems are not trained to work for marginalized group and I think that is seen through this section about being accessible for people with disabilties.

I have never seen Catch Me If You Can, but the title is familiar, so I looked at this source to see why it is a good example of social engineering. I did not know that it was a true story. It's about Frank Abagnale Jr., and as a teen, he conned people out of millions of dollars by posing as different occupations, like a pilot, doctor, and prosecutor. Then, an FBI agent makes it his mission to find Frank Abagnale Jr. and put him behind bars. In the end, Frank is caught, and he later goes on to work with the FBI to help catch other fraudsters.

My biggest concerns around privacy on social media are the lack of security that my information on social media has. In my past classes, I learned a lot about how AI and bots use the publicly available information that may seem private to their advantage. I saw this firsthand in assignment 2, when I was creating the Mastodon bot. In a few lines of code, I could collect strangers’ usernames, what they posted, and exactly when they posted it. As someone with barely any coding experience can find that information, the potential of companies and other more experienced users gathering much more sensitive information is much higher.

This source talks about the strike that union members of Kellogg went on in 2021 because the company was overworking their employee, but cutting their pay. Instead of listening to their employer's Kellogg posted job listings for the 1400 workers on strike to permanently replace them. So, online users acted in solidarity with the union workers but sending in tons of fake applications to disrupt Kellogg's hiring process. From a marketing standpoint, this is incredibly bad PR, and Kellogg handled this poorly. In my business law class, we have been hearing a lot about cases where companies acted poorly when faced with big public decisions like lawsuits and I think this is another good example.

Honestly I am not surprised with what can be done with data mining. I learned a lot about social media and technology companies and how they use their cookies and ad collection in the past year. I think that it is partly unethical, but at the same time everyone is consenting to it unknowingly. I personally don't like it, so I always choose to not allow my apps to follow my actions. I think to an extent it is helpful with targeting the right audience, but when it is done negatively like the gambling example to kids and those addicted it can be harmful. These companies are then just taking advantage of people and that is really not surprising because their end goal is to make revenue.

This is a funny source that I saw while reading the chapter in the activity example, and I did not know this had happened. I decided to click and see the reviews for myself, even if they are not from 2011. This banana slicer is a kitchen tool, and for some reason there are over 2000 reviews, many of which describe how it is a life-changing or saving product. Even the verified purchase review at the top describes a dramatic story about a medical student who saved an entire hospital from a mysterious plague through slicing bananas with the slicer. This is a good example of harmless trolling, as the reviews are not serious and do not cause harm; they are simply there to make other shoppers laugh. I think this is also good unintentional marketing, as more people are seeing the banana slicer because of the funny comments rather than the product itself.

Trolling is such a big part of social media, and I vividly remember this instance because I was a K-pop fan at the time, although I did not participate in uploading the video. I remember seeing people on TikTok and Twitter talking about the incident and how funny it was. Looking back, I find it interesting because trolling is usually seen as something negative, but in this rare case, people took the chance to turn trolling into good cause. It makes wonder where is the line drawn between being a distraction for good and being negative. This instance is a real testament to how strong fan bases are, and it reminds me of the parasocial relationships from the last chapter that help create these strong fan bases.

I see parasocial relationships in many areas on social media, but I think a lot of it is with music artists. Especially on TikTok, I see people call singers their “close friend” and address them by their first name only, as if they know them in real life. One I can specifically think of is Taylor Swift. I think she intentionally plays into it as well, like Fred Rogers, because it makes her music more relatable, and a huge part of her music is how much the lyrics relate to listeners. She also builds this relationship by hiding “Easter eggs” for fans to decode in social media posts, inviting fans to listening sessions at her home, and making fans feel like they are her close friend. Then, fans will communicate with one another on social media, deepening the relationship that others feel. Overall, this can be both positive and negative, as it can help fans feel more connected to her and her music, but it can also make fans more intense about her stance and decisions. This intense feeling is something that is seen heavily in media now with these parasocial relationships, but Taylor Swift fans are especially known for this.

I wanted to look more into this source because I really like Jennifer Lawrence personally, and I thought this was a good example. Her personality is something that viewers find relatable in the way she presents herself as a human being who is not above anyone and tells funny jokes in interviews and more. This video explains exactly what made her so popular. Her image to fans was the ultimate “cool girl,” which made her stand out from other celebrities. But further into the video, it mentions how fans began to think her persona was an act. The idea of authenticity in the chapter is highlighted through how Jennifer Lawrence was liked by fans, and that fans then felt closer to her. Then later, fans changed their view because it did not appear authentic anymore. As a fan of hers, I realized that even if it feels like I know a celebrity because of the length of time I’ve followed them or their relatability, I really do not know them, and that is the idea of parasocial relationships.

This is the source I decided to look at because this past summer I worked a lot on building my personal portfolio website through code and designed it myself. During the summer I learned a lot about UI and how everything in apps and websites is intentional to create the best experience for the user. So, this source provides a detailed explanation on what UI is, which is the area where the user and computer interact. There is also a history on how it has evolved since computers have evolved as well, starting from 1948 to the present. The gallery of the computers from the decades was the most interesting part as I could visually see how computers once were, bulky and difficult to use, and now, how they are evolving to smaller and into different aspects of life, like eyewear.

This part about the creation of infinite scroll interests me because Raskin, the creator regrets it and the outcome it created. He most likely did not think of the long-term consequences it would create for society. He thought about the reduce of friction and the technical aspects of the feature. Without the infinite scroll, many apps that are popular today would not be as effective, like TikTok or as the text mentions, Amazon, where it seems that there infinite possibilities to purchase. I think that a lot of features made in UX and overall computer engineering, people were not thinking of the human effects these features would have and that is why informatics is becoming so important. Informatics highlights the lesser thought about parts of computer interections with humans and that is why I find it interesting.

In this source, I looked at the section called "Branding", because as a marketing major, who has worked a lot with branding, I wanted to see more into X's branding. The section is focused on the logo, which has changed tremendously since changing from Twitter to X. Even from the beginning in 2006 to 2023, the logo was twitter with a blue bird, but then gradually shifted to a simplified blue bird. The iconic blue bird then changed into the current X logo with the black X. I think the shift from Twitter’s logo to X was too dramatic and disconnected the brand from its users. Even though the owner changed, the users did not, and the new branding did not keep that connection with them. I think that and other competitors like Threads (mentioned in the source) is a large reason why X has seen financial decline since becoming X. Overall, it is clear how connected people were to Twitter, as many users still call posts “tweets” even though the platform officially renamed them.

This general section of examples of python code for grouping reminded me of INFO 201, where we learned R. That class was focused on organizing existing data from spreadsheets or CSV files. So, usually the data would already be available when we implemented it into R with each row as one item and each column as a piece of information. This differs because in Python and with social media information we have to find the data ourselves and handwrite the values to equal a variable. But it is also similar because each user has the same named variables, like the names of columns in spreadsheets for R. Something else that differs is the “follows” part because it can be written in one line of code, whereas in R you could potentially need a new data table to figure out that information. Overall, looking at the differences between R and Python made me realize that data and how it is displayed is dependent of what is trying to be displayed and why it is being looked at, specifically with structuring it.

I chose this source to check out because when I was reading section 3.2.1 Friendly Bots, and saw “See a new photo of a red panda every hour,” I was intrigued by what that meant. I was not expecting it to be an X account that actually posted a new red panda photo every single hour. I love this example of a “friendly bot,” because it is so harmless and lighthearted that it is cool to see people think of something like this. I think if I saw this on my X feed, I would be really happy, and I love that that happens to others. It is also interesting to see our Bluesky bot assignment in a real instance, where someone created a bot that does what we did on Bluesky on X. Scrolling through the account, I thought about the code that was written for it, and they used something similar to sleep(). At first, I was confused about why the Bluesky bot was something we needed to do because I never thought of a use for it. Seeing this red panda X account was a funny and simple way to see our assignment brought to life.

This is interesting that social media management programs that schedule posts and other tools are considered bots. I never really thought about how it worked or what it would be considered. As a marketing major and someone who has worked with social media management tools, I always saw them as a tool for planning content in advance and looking at post analytics, but not as a bot. I've personally used Meta Business Suite the most because it is tied into Instagram and from Meta itself, so I think that's cool that Meta made a bot to help Instagram users, especially businesses. I think of it more as a supportive tool, so I wonder what other applications I use that might be bots that I do not realize. I also wonder how many other businesses or users are using social media management tools without knowing how they are created and what it means to use a bot.

This goal matters a lot to me, especially as technology and social media become more ingrained in everyday life. In INFO 200 last quarter, we learned a lot about the consequences and privacy concerns of social media and technology, including Joy Buolamwini's Unmasking AI. That book discussed a lot about how we unknowingly let technology systems control us and our biases without knowing it, as well as how that can endangers users. Another class I learned about privacy concerns in was COM 200, where we learned about the digital panopticon and how that heavily affects how users and people interact, especially online, with the ability to hide themselves. So, INFO 201 and COM 200 taught me a lot regarding how social media and technology affects user's privacy and how to mitigate it. I am excited to see how INFO 103 will connect ethics and past ideals into this new relevance of modern age with social media.

Reading the ethics in this section, something I noticed was that there wasn't much mention of Christian ethics besides in the footnote about the Divine Command Theory. Then, as a Catholic, I was interested in what ethics of Catholicism are relevant to social media. What I found was Catholic Social Teaching, which are principles that the Catholic Church has practiced since the late 1800s. In summary, it is working for the common good and solidarity with others. To society, this means not judging others and understanding how to treat people, especially the poorest or most vulnerable people. In the context of social media, this would mean the ways that platforms protect vulnerable users, like influencers in the limelight or younger demographics, and if they solely use them for profit.