24 Matching Annotations
  1. Last 7 days
  2. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. Robinson Meyer. Everything We Know About Facebook’s Secret Mood-Manipulation Experiment. The Atlantic, June 2014. URL: https://www.theatlantic.com/technology/archive/2014/06/everything-we-know-about-facebooks-secret-mood-manipulation-experiment/373648/ (visited on 2023-12-08).

      In this article, author talks about an experiment happened in the Facebook. A researcher in Facebook adjusted and investigated the posts people received and posted. He found that if people received posts with bad emotions. They would also send some posts with bad emotions. For this investigation, I would like to say it did not sent consent to the users. I have studied psychology at high school, and in psychology, researchers need to inform consent to the people they research. So, maybe this is the reason why this research is controversial。

    1. I’m no stranger to apps that help me curb my screen time, and I’ll admit I’ve often felt better for using them. But on a more communal level, I suspect that cultures of digital detox — in suggesting that the online world is inherently corrupting and cannot be improved — discourage us from seeking alternative models for what the internet could look like. I don’t want to be trapped in cycles of connection and disconnection, deleting my social media profiles for weeks at a time, feeling calmer but isolated, re-downloading them, feeling worse but connected again. For as long as we keep dumping our hopes into the conceptual pit of “the offline world,” those hopes will cease to exist as forces that might generate change in the worlds we actually live in together.

      I have experienced this before. I used up my cellular data before because of watching TikTok. So, I decided to delete it, and turn to watch TikTok on iPad which is connected internet at my dorm. Then, I don't use TikTok at outside of dorm. This do enhance my ability of studying. However, I would miss some of message from my friends. So, I change my plan. I choose to see all of the message before I sleep. This experience of mine is very related to the content in the book. In conclusion, this consequence seems like I win myself from get addicted into TikTok, but actually I win the algorithm designed to enlarge our time of using TikTok.

  3. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. Ryan Broderick. Your Least Favorite Gross Viral Food Videos Are All Connected to This Guy. Eater, May 2021. URL: https://www.eater.com/2021/5/11/22430383/why-are-gross-viral-food-videos-popular-rick-lax-facebook-watch (visited on 2023-12-08).

      This reference talks about a kind of video in Facebook. An author was taking many of disgusting video of cooking on his account, and those video spread like virus, since people felt angry when they saw those video. Then, Facebook would post to more and more people, because someone felt angry after they saw(Anrgy weigh more in the Facebook)

    1. How do you think attribution should work when copying and reusing content on social media (like if you post a meme or gif on social media)?

      For most of people including me would not get to know the history of a meme while they are using it. And this may hurt others. For example, a YouTuber burned with a disease which causes her could not grow weight, and a person made a meme about her in 2016. After this, this YouTuber sent a post about letting people get to know the story behind the meme they used. Therefore, people should try to know the story behind the meme while they are going to use it.

  4. Nov 2026
  5. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. Jeremy B. Merrill and Will Oremus. Five points for anger, one for a ‘like’: How Facebook’s formula fostered rage and misinformation. Washington Post, October 2021. URL: https://www.washingtonpost.com/technology/2021/10/26/facebook-angry-emoji-algorithm/ (visited on 2023-12-07).

      This reference talks about the recommendation formula of Facebook gives emoji of Rage 5 times of weight than emoji of Likes. In my opinion, the mechanism gives awards to people who troll. People usually give Rage emoji after they watched trolling videos. If every platform uses this mechanism, that may cause more and more people turn to do trolling behavior, since most of platform would give award to people who make the popular videos.

    1. What experiences do you have of social media sites making particularly bad recommendations for you? { requestKernel: true, binderOptions: { repo: "binder-examples/jupyter-stacks-datascience", ref: "master", }, codeMirrorConfig: { theme: "abcdef", mode: "python" }, kernelOptions: { name: "python3", path: "./ch11_recommendations" }, predefinedOutput: true } kernelName = 'python3'

      I would like to share my personal experiences of this. I usually watch TikTok when I am cleaning my face. So, I change the settings which means I will not skip any of the video the TikTok recommend to me. After this, TikTok thinks I like those video. So, I receive lots of video I really do not interested in.

  6. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. Rumman Chowdhury. Sharing learnings about our image cropping algorithm. May 2021. URL: https://blog.twitter.com/engineering/en_us/topics/insights/2021/sharing-learnings-about-our-image-cropping-algorithm (visited on 2023-12-07).

      This is a same kind of example with the automatic soap dispenser in 10.3. The reason of those kind of mistakes is because of the author. For example, the author of automatic soap dispenser may be white. So, he used his own hand to test and until he sell this machine to the public he did not find the mistake, since he is white. There may be the same in the situation of j22.

  7. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. Many of the disabilities we mentioned above were permanent disabilities, that is, disabilities that won’t go away. But disabilities can also be temporary disabilities, like a broken leg in a cast, which may eventually get better. Disabilities can also vary over time (e.g., “Today is a bad day for my back pain”). Disabilities can even be situational disabilities, like the loss of fine motor skills when wearing thick gloves in the cold, or trying to watch a video on your phone in class with the sound off, or trying to type on a computer while holding a baby.

      After reading this, I was aware that I am also situational disabilities before. One day I did not bring my earphones, when I was taking metro. Then, I cannot hear anything from my phone. So, I use subtitles in this day. However, subtitles were designed to benefit disabled people. And now everyone benefits from this. We could see subtitles benefits everyone instead of just disabled people.

  8. Oct 2026
    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).

      This article tells about the all of passwords of users could be seen by every employee. However, it should not be like this. The password of users should be secret and every employee could not see it. For me, I used same password in every platform. So, this makes me scared.

    1. What incentives do social media companies have to be careless with privacy? { requestKernel: true, binderOptions: { repo: "binder-examples/jupyter-stacks-datascience", ref: "master", }, codeMirrorConfig: { theme: "abcdef", mode: "python" }, kernelOptions: { name: "python3", path: "./ch09_privacy" }, predefinedOutput: true } kernelName = 'python3'

      For social media companies, the secrets means money to them. From chapter 8, we know that social media companies earn money from ad. So, depending on this, if most of people post their secrets on social media. That would make more people to watch this social media. Second, protecting secret of user would take so much time and money. So, according to the textbook, companies would not care about this until the bad thing happens.

  9. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. Rafi Letzter. A teenager on TikTok disrupted thousands of scientific studies with a single video. The Verge, September 2021. URL: https://www.theverge.com/2021/9/24/22688278/tiktok-science-study-survey-prolific (visited on 2023-12-05).

      This example is a common mistakes in the questionnaire, which is spurious correlations. People would receive the content they would like to watch in the Internet. So, for the questionnaire in the internet, it is possible that there is only one kind of people receive this questionnaire. And they all have same type of answer. Then, the questionnaire is invalid. So, for questionnaire in internet, they should consider that should they use data mining during the questionnaire.

    1. Do you think there is information that could be discovered through data mining that social media companies shouldn’t seek out (e.g., social media companies could use it for bad purposes, or they might get hacked and others could find it)?

      First, companies should not post immorally. For example, they should post addicted content to people who are easier to addict, like the example mentioned in the textbook about gambling. Then, posting ad. depends on interest are easier to be accept. For example, me, I have received an ad. about football, since I like football. I was happy with that.

  10. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. Film Crit Hulk. Don’t feed the trolls, and other hideous lies. The Verge, July 2018. URL: https://www.theverge.com/2018/7/12/17561768/dont-feed-the-trolls-online-harassment-abuse (visited on 2023-12-05).

      First, I agree with author's perspective. He thinks troller is like stalker, if people do not feed on them. They would do more. So, platform should ban their accounts. However, I have the question that how does the platform know who should be banned. For example, the k-pop example in the textbook. I think those kind of trolling should not be banned. Therefore, it is reasonable to ban the account of trolling, but platform should clear who should they ban and who should not.

    1. What do you think is the best way to deal with trolling? { requestKernel: true, binderOptions: { repo: "binder-examples/jupyter-stacks-datascience", ref: "master", }, codeMirrorConfig: { theme: "abcdef", mode: "python" }, kernelOptions: { name: "python3", path: "./ch07_trolling" }, predefinedOutput: true } kernelName = 'python3'

      In my opinion, it is not the best way to deal with trolling. Using bullying as an example. Trolling is as same as bullying. In situations of bullying, if you do not fight back, they would bully you again and again. It is same in the trolling. People need to use reasonable idea to say against the trolling. For example, I saw a person using lots of professional knowledge to say against the troller, and he literally could not say anything.

  11. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. https://coralproject.net/blog/the-real-name-fallacy/

      In this article, author claims that requiring users to use their real name cannot reduce the bad behavior in the community. However, the result reflects that it is no matter with using the real name. It is related to whether there is an exact rule or not. This shows using real name is a very efficient rule to manage a community.

    1. 6.4.1. Context Collapse#

      So, based of Context Collapse, many of people I meet may not real. That means different people may behave differently while they are facing different people. However, in social media it is completely different situation. Using the example in the article, a child may meet his parents when he has a meal with his friends, and he does not how to behave. In the social media, it means, different people with different background may misunderstand or don't understand what's other people posted.

    1. One famous example of reducing friction was the invention of infinite scroll [e31]. When trying to view results from a search, or look through social media posts, you could only view a few at a time, and to see more you had to press a button to see the next “page” of results. This is how both Google search and Amazon search work at the time this is written. In 2006, Aza Raskin [e32] invented infinite scroll, where you can scroll to the bottom of the current results, and new results will get automatically filled in below. Most social media sites now use this, so you can then scroll forever and never hit an obstacle or friction as you endlessly look at social media posts. Aza Raskin regrets [e33] what infinite scroll has done to make it harder for users to break away from looking at social media sites.

      No stop of users action may cause problems. If there is a small stop between posts and posts, it would be better to let users to think about the content of this video.

  12. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. What is user friction? Why you're losing users and how to stop. August 2023. URL: https://www.fullstory.com/user-friction/ (visited on 2023-11-24).

      In the article, author concludes many kinds of fiction, such as emotional friction and interaction friction. Then, author gives an example to us. It talks about users would mislead by the sign of credit card, and use it as the bottom of conforming to pay. However, in my opinion, this example did not show how bad the users' ability to operate the website. It may shows the interface of website gives wrong hint. It is related to affordances. Author of the website should check the element of website, and change the elements that looks like it could be click.

    1. 4.2.2. Counting Apples#

      In this example, we learned the number of objects could not judge it is fair or not. However, I think for different objects we should use different standard. For example, for foods, we should use weight to allocate, rather than quantity. In situation of social media, the reason why users‘ likes could not be simple. They may misclick, or just supporting their friends. If platforms want to determine what they like and recommend videos to them, those data could not be understand in this simple way(they need consider the situation I said before)

  13. social-media-ethics-automation.github.io social-media-ethics-automation.github.io
    1. My last name is to long, what do I do? June 2019. Section: Get your taxes done using TurboTax. URL: https://ttlc.intuit.com/community/taxes/discussion/my-last-name-is-to-long-what-do-i-do/00/655670 (visited on 2023-11-24).

      In this situation, one has a long last name, so he cannot type it in the system. So, he asked a question in community. Some people answered this question. For example, a person said that he can removing the last letter of his name. However, in my opinion, while a rule is not reasonable, costumer should not take this responsibility. The reason why creator of the website did not notice this question is that the user adjust the rule which is not fair. Therefore, the creator should consider names' difference, and fix the problem of system.

  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).

      After reading the store of him, I know the internet is so fake. There are so many ways people could manipulate the content in internet. For example, using bots to produce a fake conversation to show the video is popular, and using bots to increase the number of likes. However, the point is we need to learn to distinguish the content in the internet rather than just judge it depends on number of likes or comments.

    1. In 2016, Microsft launched a Twitter bot that was intended to learn to speak from other Twitter users and have conversations. Twitter users quickly started tweeting racist comments at Tay, which Tay learned from and started tweeting out within one day.

      In my opinion, this problem may caused by the programmer. They may just coding a bot which could learn what people said in the internet. However, they should let bots learn and determine it is good or bad, then there won't be this situation.

    1. Act with unforced actions in harmony with the natural cycles of the universe. Trying to force something to happen will likely backfire. Rejects Confucian focus on ceremonies/rituals. Prefers spontaneity and play. Like how water (soft and yielding), can, over time, cut through rock.
      1. For Taoism, I would like to add more information. In the textbook, it said:" Trying to force something to happen will likely backfire." It's right, but we should know more. In Taoism, spring means growing up, summer means prosperity, autumn means recession, and winter means taking a break. Therefore, the further comprehension of Taoism is understand and control. For example, ancient Chinese water wheel reflects that they can use the natural flow of water to help them cultivate, rather than forcing nature.
    1. Versions of this phrase are still around, such as in this tweet from statistician Nate Silver:

      In my opinion, in the future, Internet can be the real life. For now, some of the rule of the internet are vague. It means even if someone did impolite or criminal behavior, they would not be punished a lot. So, that makes bad people have low cost to do a crime. However, there would be more and more comprehensive law in the internet. Then, I think internet can be a real life.