20 Matching Annotations
  1. Last 7 days
    1. derstand biological evolution and how it relates to the origin of the scientific term “meme.” 12.1.1. Biological Evolution# Biological evolution is how living things change, generation after generation, and how all the different forms of life, from humans to bacteria, came to be. Evolution occurs when three conditions are present: Replication (with Inheritance) An organism can make a new copy of itself, which inherits its characteristics Variations / Mutations The characteristics of an organism are sometimes changed, in a way that can be inherited by future copies Natural Selection Some characteristics make it more or less likely for an organism to compete for resources, survive, and make copies of itself When those three conditions are present, then over time successive generations of organisms will: be more adapted to their environment divide into different groups and diversify stumble upon strategies for competing with or cooperating with other organisms.

      I find the connection between biological evolution and memes interesting. On social media, memes are constantly copied and modified, and the versions that attract more attention tend to spread further. However, I wonder whether algorithms have become a stronger influence on which memes survive than people's actual preferences.

  2. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. The Selfish Gene. December 2023. Page Version ID: 1188207750. URL: https://en.wikipedia.org/w/index.php?title=The_Selfish_Gene&oldid=1188207750 (visited on 2023-12-08).

      I think Dawkins' concept of memes provides an interesting way to understand how ideas spread through imitation. However, unlike biological genes, online memes can be deliberately modified and promoted by algorithms. This makes me wonder whether the original concept fully explains how information goes viral on modern social media.

  3. Nov 2026
    1. 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. Some recommendation algorithms can be simple such as reverse chronological order, meaning it shows users the latest posts (like how blogs work, or Twitter’s “See latest tweets” option). They can also be very complicated taking into account many factors, such as: Time since posting (e.g., show newer posts, or remind me of posts that were made 5 years ago today) Whether the post was made or liked by my friends or people I’m following How much this post has been liked, interacted with, or hovered over Which other posts I’ve been liking, interacting with, or hovering over What people connected to me or similar to me have been liking, interacting with, or hovering over What people near you have been liking, interacting with, or hovering over (they can find your approximate location, like your city, from your internet IP address, and they may know even more precisely)

      I think recommendation algorithms are useful for discovering content, but they can also create echo chambers by repeatedly showing us similar opinions. I wonder how platforms could balance personalized recommendations with exposing users to different perspectives.

  4. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. Elon Musk [@elonmusk]. Trashing accounts that you hate will cause our algorithm to show you more of those accounts, as it is keying off of your interactions. Basically saying if you love trashing *that* account, then you will probably also love trashing *this* account. Not actually wrong lol. January 2023. URL: https://twitter.com/elonmusk/status/1615194151737520128 (visited on 2023-12-07). [k6] Kurt Wagner. Inside Twitter’s ambitious plan to clean up its platform. Vox, March 2019. URL:

      I find it interesting that even negative interactions can encourage algorithms to recommend more similar content. This suggests that platforms may prioritize engagement over user satisfaction, which raises questions about how we should measure a recommendation algorithm's success.

  5. Oct 2026
  6. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. 10.6. Bibliography# [j1] Social model of disability. November 2023. Page Version ID: 1184222120. URL: https://en.wikipedia.org/w/index.php?title=Social_model_of_disability&oldid=1184222120#Social_construction_of_disability (visited on 2023-12-07). [j2] Color blindness. December 2

      I found the social model of disability interesting because it emphasizes how social and environmental barriers can create difficulties for people with disabilities. I agree with this perspective because improving accessibility in technology and public spaces can help reduce these barriers and promote inclusion.

    1. 10.2.1. Coping Strategies# Those with disabilities often find ways to cope with their disability, that is, find ways to work around difficulties they encounter and seek out places and strategies that work for them (whether realizing they have a disability or not). Additionally, people with disabilities might change their behavior (whether intentionally or not) to hide the fact that they have a disability, which is called masking and may take a mental or physical toll on the person masking, which others around them won’t realize. For example, kids who are nearsighted and don’t realize their ability to see is different from other kids will often seek out seats at the front of classrooms where they can see better. As for us two authors, we both have ADHD and were drawn to PhD programs where our tendency to hyperfocus on following our curiosity was rewarded (though executive dysfunction with finishing projects created challenges)[1]. This way of managing disabilities puts the burden fully on disabled people to manage their disability in a world that was not designed for them, trying to fit in with “normal” people.

      I think it's unfair that people with disabilities often have to adjust their behavior to fit into environments that weren't designed for them. Instead of expecting individuals to constantly adapt, schools and workplaces should make accessibility a priority so everyone can participate comfortably.

  7. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. 9.2. Security# 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, the proper security practice for storing user passwords is to use a special individual encryption process [i6] for each individual password. This way the database can only confirm that a password was the right one, but it can’t independently look up what the password is or even tell if two people used the same password. Therefore if someone had access to the database, the only way to figure out the right password is to use “brute force,” that is, keep guessing passwords until they guess the right one (and each guess takes a lot of time [i7]). But while that is the proper security for storing passwords. So for example, Facebook stored millions of Instagram passwords in plain text [i8], meaning the passwords weren’t encrypted and anyone with access to the database could simply read everyone’s passwords. And Adobe encrypted their passwords improperly and then hackers leaked their password database of 153 million users [i9]. From a security perspective there are many risks that a company faces, such as:

      I find it surprising that even major companies like Facebook have failed to protect users' passwords properly. I think companies should be held more accountable for basic security practices, especially when millions of users trust them with personal information.

    1. Jacob Kastrenakes. Facebook stored millions of Instagram passwords in plain text. The Verge, April 2019. URL: https://www.theverge.com/2019/4/18/18485599/facebook-instagram-passwords-plain-text-millions-users (visited on 2023-12-06).

      The Verge article about Facebook storing millions of Instagram passwords in plain text shows how serious poor security practices can be. It makes me wonder whether companies should face stricter penalties for failing to protect user data.

    1. Choose Social Media Platform: Bluesky | Reddit | Discord | Mastodon | No Coding We’ve been accessing Bluesky through Python and the “atproto” code library. The atproto code library works by sending requests across the internet to Bluesky, using what is called an “application programming interface” [h3] or API for short. APIs have a set of rules for what requests you can make, what happens when you make the request, and what information you can get back. If you are interested in learning more about what you can do with atproto and what information you can get back, you can look at the official documentation for those. But be warned they are not organized in a friendly way for newcomers and take some getting used to to figure out what these documentation pages are talking about. So, if you are interested, you can look at the atproto library documentation [h4] to find out what the library can do (again, not organized in a beginner-friendly way). You can learn a little more about what actions the client can do here [h5]. You can also reference some official example programs [h6].

      I think it's interesting how APIs allow us to collect and analyze social media data using Python. Since I'm also learning data programming, I can see how this could be useful for studying user behavior and online trends. However, I wonder how platforms can balance data accessibility with user privacy.

  8. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. Kurt Wagner. This is how Facebook collects data on you even if you don’t have an account. Vox, April 2018. URL: https://www.vox.com/2018/4/20/17254312/facebook-shadow-profiles-data-collection-non-users-mark-zuckerberg (visited on 2023-12-05).

      I found this article interesting because it shows that social media platforms can collect information even about people who don't have accounts. This raises concerns about privacy and consent, since people may not even realize their information is being collected. I think users should have more control over how their personal data is used.

  9. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. Quinn Norton. Anonymous 101: Introduction to the Lulz. Wired, November 2011. URL: https://www.wired.com/2011/11/anonymous-101/ (visited on 2023-12-05).

      The Wired article about "the lulz" highlights how entertainment can motivate online trolling. I find it interesting that something considered funny by one group can be harmful to others. This raises questions about where humor ends and harassment begins.

    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.

      I assume that people often troll because they enjoy getting attention and feeling powerful online. However, even if they consider it a joke, their actions can seriously hurt others. I believe anonymity makes this behavior even more common.

  10. 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.

      I think authenticity is essential for building trust online. The lonelygirl15 case shows how easily people can be misled by seemingly genuine content. It makes me wonder whether we can ever fully trust what we see on social media.

  11. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. Peter Aldhous. At First It Looked Like A Scientist Died From COVID. Then People Started Taking Her Story Apart. BuzzFeed News, August 2020. URL: https://www.buzzfeednews.com/article/peteraldhous/bethann-mclaughlin-twitter-suspension-fake-covid-death (visited on 2023-12-07).

      The BuzzFeed News investigation highlights the importance of fact-checking. It's concerning how a fabricated identity and false COVID-19 death could gain widespread sympathy before anyone questioned the story's authenticity.

  12. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. Tom Standage. Writing on the Wall: Social Media - The First 2,000 Years. Bloomsbury USA, New York, 1st edition edition, October 2013. ISBN 978-1-62040-283-2.

      I find it interesting that Tom Standage traces social media back thousands of years rather than treating it as a modern invention. This suggests that people's desire to share information and connect with others has remained consistent throughout history,

    1. As we’ve looked through the history of social media platforms, we’ve seen different ways of making them work, such as: How you can send messages to other people? Will these messages be public or private? Does the user have to refresh the site to check for messages, or does the message automatically appear, or perhaps even make their phone buzz? What restrictions are there on the content of messages sent? What information can a user provide about themselves in a profile? etc. Let’s look at some of these design decisions more closely:

      I think the way social media platforms handle notifications significantly influences user behavior. For example, instant push notifications encourage us to check our phones frequently, sometimes even when the messages aren't important. This makes me wonder whether platforms should prioritize user well-being over maximizing engagement by allowing users more control over notifications.

    1. In addition to representing data with different data storage methods, computers can also let you add additional constraints on what can be saved. So, for example, you might limit the length of a tweet to 280 characters, even though the computer can store longer strings. There are many places these constraints might be used such as: for an age (integer), only allow ages between 0 and 120 for a country name (string), have a pre-set list of valid country names for a legal name (string), disallow emojis

      I think data constraints are essential for maintaining data accuracy. For example, limiting ages to 0–120 prevents unrealistic entries and makes datasets more reliable for statistical analysis.

  13. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. Julia Evans. Examples of floating point problems. January 2023. URL: https://jvns.ca/blog/2023/01/13/examples-of-floating-point-problems/ (visited on 2023-11-24).

      I find floating-point precision issues interesting because even simple decimal calculations can produce unexpected results in Python. This shows why we need to be careful when comparing floating-point values in data analysis.

  14. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. Sean Cole. Inside the weird, shady world of click farms. January 2024. URL: https://www.huckmag.com/article/inside-the-weird-shady-world-of-click-farms (visited on 2024-03-07).

      I find the topic of click farms really interesting because it raises questions about how much we can trust online engagement. We often assume that likes, views, and followers reflect genuine popularity, but they can also be artificially manipulated.

    1. In a computer program, when you save information for later use, instead of putting it in a bowl, you give it a name. The computer then makes a place in its memory with that name, and saves the information you asked it to save. Then you can use that name later in the program to ask the computer what was saved in that spot.

      I think comparing variables to mixing bowls is a helpful analogy for understanding programming. I've learned Java and Python before, and this reminds me of how variables store information that we can reuse or update throughout a program. It also makes me think about how choosing meaningful variable names can make code much easier to understand.