This article explain what is "corner a market" means. It refers to acquiring a substantial amount of shares or a significant commodity position to manipulate its price. This practice requires considerable financial resources and can involve accumulating major shares of economic activity in a particular sector. Large institutions may legally corner a market, gaining a competitive edge, but they often face scrutiny from regulatory bodies. However, illegally cornering a market disrupts competitive price discovery and can necessitate regulatory intervention.

If government regulations banned social media sites from monetizing personal data and targeted advertising, they would need to adopt alternative business models. Possible alternatives include subscription-based models, where users pay for access, ensuring privacy but potentially limiting access.

Archbishop Desmond Tutu's philosophy of ubuntu highlights our deep interconnectedness and the need for strong communal bonds. He championed restorative justice over retributive justice, especially in the context of post-apartheid South Africa. Tutu believed that apartheid harmed both its victims and its beneficiaries, calling for acknowledgment of past wrongs and material reparations to achieve true reconciliation. While some critics argue that his approach let white beneficiaries off too easily, Tutu insisted that real reconciliation demands genuine efforts to make amends. His concept of ubuntu, influenced by his Christian faith, values forgiveness and interdependence rather than the Western focus on individual autonomy. Tutu's views on justice, harmony, and human dignity provide valuable insights for promoting social justice and unity worldwide.

To retract a tweet, users would simply click a "Retract" button next to their tweet. They'd get a prompt asking for confirmation. They could then choose to either keep the original tweet visible with a clear "Retracted" label or hide the tweet content while still showing a retraction notice. Users could add a brief explanation for why they're retracting the tweet and include links to correct information. This feature helps users address mistakes or apologize without making it seem like they’re trying to hide their past posts.

This article points out the importance of understanding the demographics and engagement patterns on social media platforms like Twitter, especially regarding their impact on public discourse and political narratives. This article is mainly about discussing the characteristics and behaviors of U.S. adult Twitter users compared to the general public. It reveals that Twitter users are younger, more educated, and more likely to identify as Democrats. Additionally, it indicates that a small group of Twitter users contribute a significant portion of tweets, showing the disparity in users' engagement levels.

I think social media platforms should implement clear guidelines and effective moderation tools to encourage good crowdsourcing. The platform's rule should outline acceptable behavior and consequences for violations. Also, active community engagement, including incentives for quality contributions and education on responsible online behavior, can be effective. In addition, transparency about data usage and decision-making processes builds trust and encourages users to participate positively.

The article addresses misconceptions about autism being a gradient rather than a true spectrum. This article also use vivid analogies like the visible light spectrum to illustrate its point. It highlights the diversity within autism by explaining how different individuals can have unique combinations of traits, emphasizing that autism is not just one condition but a complex collection of related neurological conditions. The author thinks we shouldn't compare different types of autism as "more" or "less" severe, and emphasizes the importance of understanding individual strengths and challenges rather than making assumptions based on outward behaviors.

I believe that social media platforms hold a substantial responsibility for the mental well-being of their users. I've noticed the impact they can have on mental health when using social media platforms, from comparison-induced anxiety to exposure to harmful content. Therefore, it's necessary for platforms to prioritize user safety by implementing effective content moderation, promoting positive online interactions, and providing accessible mental health resources. Additionally, transparency about algorithms and data usage also plays a crucial role in building trust and ensuring ethical practices.

This source dives into the experience of content going viral and underscores the complexities of virality, showing how what starts as an exhilarating rush can quickly turn overwhelming or even dangerous. This article also prompts questions about the responsibility of platforms and authors in dealing with the consequences of going viral, where online harassment is an important aspect.

While I didn't necessarily create viral content myself, I have participated in sharing videos and reposting posts. I think sharing and reposting helps the content be suggested to other users whom the algorithms think have similar interests to me. Additionally, I noticed that the watching completion rate for videos is also a big factor for video platforms' algorithms to evaluate the quality of the content and therefore determine if the system will suggest the video.

This source is talking about Facebook's default setting that allows anyone to look up a user profile based on the phone number used for two-factor authentication has sparked concerns about privacy and security. Users are unable to opt out of this setting, leading to criticism about Facebook's use of phone numbers as a unique identifier across platforms and its potential impact on user privacy. This article actually makes me wonder about the balance between security measures and user privacy. The question is, how can platforms like Facebook ensure both security and privacy without compromising one for the other?

My favorite recommendation is for discovering relevant content based on interests: Social media platforms often use algorithms to analyze users' activities, likes, and interactions to recommend content that aligns with their interests. This can lead to users discovering valuable information, products, or communities they are interested in.

This Wikipedia page introduces Assistive technology (AT), which is a term for assistive, adaptive, and rehabilitative devices for people with disabilities and the elderly. It's surprising to read how the deign of AT also involves considerations of the potential mental challenges brought by physical disable, and these are all good examples of how technology is beneficial to society.

One interesting aspect is how people may unintentionally hide their disabilities through masking behaviors, which can take a toll on their mental and physical well-being. And this is very commonly seen and normalized in daily life where people adapt their behavior to fit societal norms and expectations, often concealing their struggles. One question that arises from this discussion is how we can create more inclusive environments that don't place the burden solely on individuals with disabilities to adapt. This involves consideration of how societal structures and attitudes can either support or hinder people with disabilities in their coping strategies and overall well-being.

The article discusses Facebook's decision not to notify more than 530 million users about a data breach that exposed their personal information. This breach included phone numbers, names, and locations and was attributed to malicious actors exploiting a vulnerability on the platform. The lack of notification has raised concerns about data privacy and user protection. This incident emphasizes the ongoing challenges companies face in safeguarding user data and maintaining transparency regarding data breaches, highlighting the need for robust data protection measures and clear communication with users about their privacy.

I think the biggest incentive is the profit motive for companies. Collecting and monetizing user data is a significant source of revenue for these companies. The more data they have access to, the more targeted and valuable their advertising services become. This can lead to a temptation to prioritize data collection and utilization over privacy concerns. They also consider the user's perspective, users often value convenience, personalized experiences, and free services offered by social media platforms. This creates an environment where companies may believe that users are willing to trade some privacy for these benefits, leading to a culture of data collection without sufficient transparency or user control.

The article talks about some strategies that individuals can use to reclaim control over their data. I think the most essential part of this article is about introducing concepts like data strikes, data poisoning, and conscious data contribution as ways to exploit the importance of good data for algorithms. It also mentions the need for further research and policy frameworks to support these initiatives effectively. This article generally encourages a proactive approach from individuals and researchers to address data privacy and influence algorithmic behaviors.

I think data mining by social media companies could raise ethical concerns due to many aspects. This could include potential privacy violations, security risks like data breaches, biased results, and lack of transparency. Therefore, companies must prioritize user privacy and security to ensure responsible and ethical data mining practices and prevent misuse of personal information.

This sourced discussion the Nazi problem behind "my little pony". It discussed the Nazis problem come in when it’s edgy and provocative to be an adult obsessed with cartoon ponies. My Little Pony fans primarily express their enthusiasm for the show by sharing their own cartoon drawings of the main characters, which they usually upload to the image boards.

I believe in most situations, the "don't feed the troll" rule is the most common and effective way for individuals to protect themselves on the internet from the trollers. However, in terms of dealing with trolling in a larger aspect and regulating trolling, it takes the social platforms' effort to create a more complete policy.

In this article, David Robinson uses programming to compare the tweets from Trump's iPhone and Android phone and concludes that tweets from the iPhone are sent by his team and tweets from the iPhone are his own writings. He analyzes the tweets from several perspectives including time sent, frequent words, emotions, amount of pictures included, etc. And I personally think the perspectives he selected are very persuasive and the results of his analyses strongly support his guess.

I think this part is very interesting, especially considering the lack of formal institutions compared to nowadays. So I wonder how trust and authenticity were built and maintained in early nomadic societies. Are there any specific mechanisms they employed to ensure authenticity within their communities?

This resource brings up a very important aspect that we need to consider when developing a social media platform. Depending on the focus of the platform these resources introduce several factors that lead to user friction. However, while fixing the user friction, this source discusses some potential benefits and positive sides of having user friction which I think is inspiring.

When the use case comes to creating in-depth discussions, one example for this question would be Instagram. Instagram's visual-centric platform with limited text space makes it difficult to host extensive text-based discussions or debates. So it might not be the most ideal platform for those seeking in-depth discussions.

As models are created based on a huge amount of data, there's a lot of simplification of data and sometimes wrong data will also be considered. This reminds me of when I studied microeconomics in high school and applied different economics models to real-life scenarios. It turns out that the modeled, idealized results can be very different from the actual result as there are so many other factors in real life besides the idealized situation in models.

I think what we always prefer to overlook are things that we personally think don't matter and therefore subjectively assume it's also not harmful to others. For example, sometimes people might add personal understanding when quoting someone else's opinion without malicious intention and I think this can be considered "pernicious ignorance".

I found an interesting explanation of API: In a restaurant scenario, the server serves as the API, acting as the intermediary between the customer (client) and the kitchen (server). The menu represents the API's endpoints and functionalities, providing options for the customer to choose from. When the customer orders, they request the server (API), specifying their desired action. The server then processes the request(sent to the kitchen), performs the necessary operations, and returns the response to the customer(the food they want), completing the interaction.

I think people's expectations for a bot and a "normal" user might differ in terms of interaction style, accuracy, and capabilities. An example is online customer service. When a user contacts a customer service chatbot, they typically expect quick and straightforward responses to their requests. But if they reach out to a human customer service rep, they might potentially expect a more personalized interaction. For example, they might want the rep to show empathy toward their concerns, provide detailed explanations, etc.

This ethical principle from Confucius emphasizing reciprocity as a guiding principle for ethical conduct, strikes a chord with me due to its simplicity and universality. I'm really impressed by how a principle in ancient times is still valuable in modern society. So I'm interested in how Confucius's idea navigates modern complexities and how it addresses some ethical topics nowadays like digital ethics in social media

While consequentialism gives a clear and pragmatic way to ethical decision-making by focusing on the results, it's controversial. Because it can potentially overlook the complexities of moral dilemmas and may fail to fully consider the nuances of intention and intrinsic value inherent in ethical decision-making. Additionally, one of the cores of this ethical framework "the ends justify the means" can be challenged on moral grounds because it only prioritizes achieving the best result without thinking from different perspectives and considering others' rights.