12 Matching Annotations
  1. Last 7 days
  2. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. FBI–King suicide letter. November 2023. Page Version ID: 1184939326. URL: https://en.wikipedia.org/w/index.php?title=FBI%E2%80%93King_suicide_letter&oldid=1184939326 (visited on 2023-12-05).

      I looked into the FBI–King suicide letter source, and it was disturbing to learn that the FBI anonymously sent Martin Luther King Jr. a threatening letter encouraging him to end his life. I believe it shows how communication tools can be used by powerful institutions for harassment, intimidation, and psychological pressure, not just by random individuals online. I think this source shows that trolling and manipulation have existed long before social media, but technology can amplify them.

    1. 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 [g6]. 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 [g5]. 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.

      This section made me think that trolling is often less about the topic itself and more about getting attention, power, or reactions from others. I’ve seen people post obviously provocative things just to make others angry. It also seems like social media rewards trolling because outrage often gets the most engagement.

  3. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. Text analysis of Trump's tweets confirms he writes only theAndroid half was published on. Text analysis of Trump's tweets confirms he writes only the (angrier) Android half. August 2016. URL: http://varianceexplained.org/r/trump-tweets/ (visited on 2023-11-24).

      This article shows that data analysis can reveal patterns in behavior that aren’t obvious at first. One interesting detail is how the tweets from Android were more aggressive compared to those from iPhone, suggesting they were written by different people. It made me think about how much we can learn from metadata, not just what is said but how and where it is posted.

  4. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. Early in the days of YouTube, one YouTube channel (lonelygirl15 [f1]) started to release vlogs (video web logs) consisting of a girl in her room giving updates on the mundane dramas of her life. But as the channel continued posting videos and gaining popularity, viewers started to question if the events being told in the vlogs were true stories, or if they were fictional. Eventually, users discovered that it was a fictional show, and the girl giving the updates was an actress. Many users were upset that what they had been watching wasn’t authentic. That is, users believed the channel was presenting itself as true events about a real girl, and it wasn’t that at all. Though, even after users discovered it was fictional, the channel continued to grow in popularity.

      The lonelygirl15 example shows how people can feel genuinely betrayed even if the content itself is entertaining. I think this is because people aren’t just consuming content, they’re building trust with the person behind it. When that trust is broken, it feels more personal. It also made me think about influencers today, where it’s sometimes unclear what is real and what is staged. Even if the content is enjoyable, knowing it’s not authentic changes how I feel about it.

  5. Apr 2026
  6. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. Web 2.0. October 2023. Page Version ID: 1179906793. URL: https://en.wikipedia.org/w/index.php?title=Web_2.0&oldid=1179906793#Web_1.0 (visited on 2023-11-24).

      The Web 2.0 article explains how the internet shifted from mostly static pages in Web 1.0 to more interactive platforms where users create and share content. What stood out to me is how this change is what influenced and made modern social media possible. Platforms like X (Twitter) or Instagram depend on user participation, not just information being posted by a few sources. I believe it shows why social media today is faster-moving and more dynamic compared to other forms of media.

    1. 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

      I think this part shows that social media behavior hasn't really changed, only the speed and scale have. People were already sharing rumors and sharing updates before the internet, just through either pamphlets or graffiti. But today, we often blame social media for misinformation, but these patterns have always existed, just in a different form. I think the main difference is that it can spread much faster and reach a wider audience.

  7. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. Zero-based numbering. September 2023. Page Version ID: 1176111995. URL: https://en.wikipedia.org/w/index.php?title=Zero-based_numbering&oldid=1176111995#Origin (visited on 2023-11-24).

      Zero-based numbering was interesting because it feels confusing at first to start counting from 0 instead of 1 . But it actually makes sense in programming since it matches how computers organize data. It made me realize that systems are often designed for how computers work, not how people naturally think, which can make things harder to understand.

    1. 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.

      As I read through this part, I learned how metadata can be just as important as the actual content. For example, the number of likes or who posted something can completely change how people interpret a post. I’ve noticed that I’m more likely to trust or engage with posts that already have high engagement, even if the content itself isn’t that meaningful.

  8. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. Steven Tweedie. This disturbing image of a Chinese worker with close to 100 iPhones reveals how App Store rankings can be manipulated. February 2015. URL: https://www.businessinsider.com/photo-shows-how-fake-app-store-rankings-are-made-2015-2 (visited on 2024-03-07).

      The Business Insider article about click farms was interesting because it showed how manipulation on social media doesn’t always come from bots, but from coordinated human labor. What stood out to me is how scalable this is. Because in the photo, one person managing dozens of devices can artificially boost engagement and rankings. It made me think about how hard it is to distinguish “real” popularity online, since both bots and human-run systems can create the same effect.

    1. There are several ways computer programs are involved with social media. One of them is a “bot,” a computer program that acts through a social media account. 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. Bots, on the other hand, will do actions through social media accounts and can appear to be like any other user. The bot might be the only thing posting to the account, or human users might sometimes use a bot to post for them. Note that sometimes people use “bots” to mean inauthentically run accounts, such as those run by actual humans, but are paid to post things like advertisements or political content. We will not consider those to be bots, since they aren’t run by a computer. Though we might consider these to be run by “human computers” who are following the instructions given to them, such as in a click farm:

      I find it interesting how the definition of a "bot" depends on whether the actions are automated by code or done by humans following instructions. In addition to that, the idea that click farms are like human computers blurs the line between automation and human behavior for me. For example, if both bots and click farms can manipulate engagement or spread information, should we treat them differently just because one uses code and the other uses people?

    1. When scientists wanted these human computers to do a task for them, they would give these human computers instructions for what they wanted calculated. These instructions were given in a regular human language (like English), and in math notation. Then the human computers would send back the results of whatever calculation they had been asked to perform. But human computers were eventually replaced by electronic computers, and communication with electronic computers was not straightforward.

      I realized that computing has always been about communication, rather than just calculation. Even before machines, people had to give clear instructions to human computers, which is similar to how we write code today. What specifically stood out to me was how this work was often done by women, but their contributions are rarely recognized in discussions about technology.

    1. 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.

      Although deontology focuses on morals here, the one thing I find limiting about it is that it focuses heavily on rules without always considering real-world consequences. For example, during the lecture we had on Apr 1st, in situations like the Alzheimer's case we discussed, strictly following a rule like respecting autonomy might actually put someone in danger. So while deontology provides clear guidance, it can sometimes feel too rigid when situations are complex.