This article shares the impact of social media posts on prolific.com. Prolific.com is a scientific survey platform that pays users to fill out surveys to be used in a scientific study for university like Stanford, reasearch labs, etc. In July 2021, a Tik Tok user posted a video that got 4.1 million views sharing that doing surveys on Prolific is an easy side hustle to make money. The website was then flooded with responses from young adult woman which skewed the data and results of multiple studies.

This tweet I found both funny and scary. Funny because it is true. I think it is scary because tech company's using the name of ethically bad fictional sci fi technologies or items takes away the message authors are trying to convey. Instead of readers seeing these technologies as bad as the author tries to do, they are more likely to think, "This technology is something I already use in my day-to-day life, it's not as bad as the author is trying to say."

I think public shaming is bad when a large group is targeted for an aspect of themselves they cannot change. This means shaming someone for their race, gender, sexuality, etc. If you are shaming someone for something publically the shame should be placed on an action the of an individual theycan be held accountable for rather than something they cannot change.

The wikipedia Face (sociological concept) article defines "face" in associate with morality and honor. Face in English is similar to many other expression globally that all roughly translate to "loose face," "save the faces water," etc. In english, we often use the expression save face as our usage of using face in an expressoin.

This Buzzfeed article shares the findings of a study completed by Bot Sentinel, a twitter analytics bot. The bot analyzed 114,000 negative tweets about the Duchess and Duke of Sussex, Meghan Markle and Harry. The results showed that about 80 accounts were responsible for 70% of the negative tweets about the couple. Of these 80 accounts, there were 55 primary accounts that did the majority of the hate tweeting and 28 secondary accounts. The secondary accounts assisted the primary accounts by retweeting and responding to the primary accounts and posting their own negative tweets. These 80 accounts were able to post enough tweets that their negative message about Harry and Meghan spread to over 17 million other Twitter users.

I think crowd harassment is a grey area of social media. Even when crowd harassment is targeting an individual who did something awful I think the outcome of the mass tweeting, posting, etc against that target can draw more attention to the person which then brings more defenders even when the target initially had no one supporting them, but people always like to go against the crowd. For the targets, especially billionaires, cults, or groups, "any publicity is good publicity" thus getting their name out there to a wider audience. Additionally, I see sometimes crowd harassment that initially comes to be to contradict a bad action, is turned into a trend or a joke thus taking away from the intial reason for the protest that caused the crowd harassment.

GoFundMe is a application used for fundraising. A user can post the reason why they need money and any person, logged in or logged out, can contribute money to their fund. Thus the name GoFundMe because the website is a place someone can go to ask for funds for themselves. The users who place posts on GoFundMe are then able to share the post with contacts in their phone, by email, or by any social media platform by sharing the link. This can cause a chain of spreading the fundraising effort and contribute to many donations. I personally have donated to multiple GoFundMes.

I think crowdsourcing is especially interesting in the context of the previous chapter on content moderation. Meta changed their content fact checking policy to be user forums rather than content moderators checking for factual posts. The social media comapany is crowdsourcing fact checkers rather than trusting real information.

This reuters article reveals the content moderation issue Facebook faces. Facebook, at the time of the articles publication, supports 111 different languages. The issue with moderation arises from this large number of languages. Facebook has to have moderators who monitor all these languages for an content issues and additionally there are more than 111 languages so users who make posts in a non-supported language create a gap in content moderation. This issue has fostered an enviroment of harmful content in previous elections in the South Pacific and dominating hate speech in nations that speak Khmer.

Tree structure for comments is helpful for understanding the concept of comments. The tree structure reminds me of the the previous coding topics: conditional statements and lists. Lists because each branch of a tree is like an ordered list of comments that are interconnected. Conditional statements because if a user responds to another comment it is added to a list.

This CNBC article outlines the depression study UCLA has started with help from Apple, specifically their health products like apple watches, sleep data, and fitness goals. The study will track 150 participants for 3 years and see how their health data relate to their mental health. This article is interesting in the context of the previous lesson of data mining that outlines what data organizations try to collect about users because some of the information is directly correlated to large-scale research studies.

Social Media has been bad for my mental health in more ways than good for my mental health. The biggest benefit of social media is the ability to stay in contact with friends who live in different cities, attend different universities, etc. In contrast, social media creates invisible social rules and expectations. For example, commenting on individual's posts. There is an expectation that you like and comment on a friends post and if you don't it seems rude. These rules make social media sometimes feel more like a chore than a fun place to connect with long distance friends.

This buzzfeed articles recounts a viral moment on the social media platform, tik tok. In late 2020, a creator posted a parody romance song about a couple fighting in a grocery store. Since this was posted at the height of quarantine during the COVID pandemic, the use of social media was higher. When another creator used the diet feature on tik tok to add instrumentals to the original post, they started a viral trend of adding a personal spin to the original post and adding to the chain of users dueting the post. Over the height of the trend over 500 users dueted the post.

I have grown up in a time where viral moments on social media have become points of connection between my generation. The language used is derived from viral moments. For example, using the word “slay” is used commonly by people my age, but people older or younger than me by more than a few years use different phrases from social media moments that were viral for their age group. Viral moments can connect generations but also widen the gap between one age group and another.

Facebook automaticallys users phone numbers to connect their accounts, sometimes without explicit consent. The reason is for 2FA, but many security risks occur for high risks account if they have to publicize their phone number. For example, sim card switching or stealing. This furthers the structure of control facebook creates. Users want a choice to opt out of phone number connection and FaceBook is exerting control by not allowing them to.

Overtime, Instagram's algorithim for post displaying has become irrelevant to an user. Not only when I post do none of my friends who follow me see the posts when I share content nor do I see what my friends post. Since the algorithim shifted from a time based display, the posts seen are so much more advertisement heavy rather than related to the people I follow.

The General Data Protection Regulation (GDPR) is how the European Union safeguards citizens personal data. The regulation was implemented in 2018 and follows a opt in policy for online platforms getting access to personal data. This is unlike the USA, where individuals have to opt-out of cookies. The GDPR outlines privacy policies for different organizations, individuals, and countries.

The case studies of password leaks and security issues highlights the human error component of security vulnerabilities and attacks. For example FaceBook storing passwords in plain text is secure if the only people who can access the database with passwords are the people whos passwords they are. In theory this should work but mistakes and bad actors may access the passwords ruining the protection of the storage.

This Good Housekeeping article by Lindsey Murray gives a brief overview of what information facebook store about a user before providing a step-by-step walk through on how to find the information FaceBook has about yourself. Facebook mines a lot of personal data a user wouldn't expect with the reasoning of targeted marketing. These classifier categories include: your phone type, primary browser, job, family members, US Politics, Medical and Healthcare information, and generation classification (i.e Millenial), and so much more. Facebook has a lot of information store on a user and the article then explains how you can find exactly what information is stored about yourself. This article was written in 2017 and is still relevant to today.

These example of what information are mined about social media users is interesting in the context of Chapter 7. Trolling. For example, if a troll mines data about user in the context of their political leanings, they may use tactics that target their political interest. The use of data mining can be useful in other social engineering attacks like phishing or deepfakes because the bad actor can understand their victim and use that information to seem like a more trustworthy source.

I have witnessed trolling. I think in a day where social media is so popular trolling has become normalized because individuals can hide behind a username to make a comment about someone. Most trolling cases I see are with celebrities online because they have a large preseence and garner attention from trolls because of their following. Trolls will comment on their lifestyle choices in the comments of their posts or tag them in a video saying awful things about the individual. I think a good example of celebrities being trolled recently is a Blake Lively-Justin Baldoni drama. I agree with the rules of internet protocol to ignor trolls. Responding gives them attention which gives the trolls more power.

The rules of the internet is a list of social rules for internet users developed in 2006. The list was originally created for the hacker group, Anoynmous, but spread to forum websites like 4chan. When it was archived the list contained 18 rules, but these protocols were part of 48 rules.

Jackson uses python to prove that Donald Trump's team tweets from an iPhone, while Trump himself curates tweets on an android phone by analyzing the tone, punctuation, use of pictures, etc by tweets posted from the two devices. One thing that stood out to me from this article was the analysis of the words in the Android/Trump created tweets. The words in his tweets were 40-80% more likely to have negative associations like disgust, anger, fear, or sadness.

Parasocial relationships can provide comfort especially to children such as your sister. Many cartoon tv shows I watched growing up, like Dora the Explorer have the characters break the fourth wall and talk directly to the viewers. These direct questions asked made me be more involved watching Dora and do things like practice my counting, learning novice Spanish, and searching the screen for swiper the fox when Dora asked where he was. The relationship aided in my learning.

Parasocial relationships become inauthentic and an issue when the parasocial relationship takes prioritiy over the ones you have in person.

This wikipedia page shares the definition, use cases, and importance of affordances in application design. An affordance is a visual that tells a user of the features purpose without explicitly stating it. For example, arrows on a screen facing left and right indicate to the user "go back a page" and "next page" without explicitly stating "click this arrow facing to the right to go to the next page." One thing that stuck out to me from this article, was saying affordances are synonymous with signifiers as an affordance signals what a user should do.

The connection between the history of social media before the internet and modern internet social media is interesting to me because you see the usage of words from handwriting and delivering media. For example, sharing a photo on Instagram is called sending a "post." SImilarly if you wanted to mail a letter you would bring it to a post office to share.

voluntourism = volunteering + tourism

I have never heard of this word combination, but I am familiar with the actions the Kinder World articles describe. I have seen on social medias posts of individuals going to volunteer and posting about how they made a great impact. The issue, that I especially find interesting with the rise of generative image AI is that these images, if the user allows permissions, can be used as training data and then the perspective of a place or country can be skewed to seem like they all match that of a selfie someone took on a voluntourism trip.

Even though social media is used by a diverse population of people who have independent biases, perspectives, and beliefs, the biases ingrained in the systems are the ones of who developed the technology. The same goes for bots, the biases are based on what the developer thought vital to add as gaining utility, but the perspectives vary person to person leading to biased and ignorant interactions.

Bots are automated to perform a specific task. Human users in comparison are subject to emotions and error. These emotions allow users routines on social media to vary and change, while a bot complete a specific task without be influenced by anything other than code. This makes them great for executing tasks like deleting old tweets or identifying something.

As an avid Star Wars fan, I counted down the days until the Last Jedi was released. After seeing the movie, I was content with the storyline and invested in the different action shots. I was suprised when I saw the amount of hate the film recieved. While it was not the best movie in the Skywalker saga (that title goes to Empire Strikes Back), it was still a good, action-packed movie. Learning the amount of bots that were used to create these reviews is quite interesting to me. Star Wars originally created as a political statement following Nixon's presidency so that it was now being used as a political weapon in a different sense of comments is on the contrary to the film's original goal

These two questions are extremely relevant, especially as AI and social engineering grows more prevalent in social media platforms. AI is being used to spread disinformation or misinformation to large crowds of people. For example, during the 2024 election. Donald Trump used AI generated images to exaggerate the celebrity support he had and natural disasters in the US. His use of AI to convince people of false information was extremely dangerous because individuals did not see the difference between real life and the social media posts they were viewing. While Social Media can be great to connect with a large network of people. For example, I am able to keep in contact with friends from middle school who now live in different countries, it is also exteremly scary because individuals can use the widespread tech to share manipulated or fake content.

Egoism is interesting because it implies in the goal that if everyone does what will maximize their own net good, overall the goodness in the world outweighs the evil. But every culture, person, and place has it's own relative perspective on what goodness is and what the goodness that one ought to do includes. This makes the entire theory relative because it is subjective.