# Reading Responses Set 2

## Reading Responses 1 out of 5

### March 20 - Ads & social graph background
[Google Doc Link](https://docs.google.com/document/d/1UUib_beRuOdrdoM9v7pdUg0khs3daw_-hmEKIzUgWeg/edit?usp=sharing)
Online advertisements have been more sophisticated than ever as in takes forms in many different ways across the internet. Developers place these advertisements strategically to capture an individual’s attention to click on it or spend time looking at it. Both of which generate revenue for the developers. From the video from Vox and the article, it is apparent that online advertising is not confined to a single format. This raises an important question about the safety of information from public users as they access these website platforms. Just how much information about a certain individual do tech companies have?
One of the most common types of online advertising is displayed on platforms. For example, opening up a website such as the NY Times instantly has a banner advertising products and companies. According to the reading, banner ads are graphic images or animations that are
deliberately placed on website pages to draw attention (Stokes 2013). Even the banner’s size is chosen carefully. Other famous advertising methods include geo-targeting, network targeting, connection targeting, day and time targeting, social serving, behavioral targeting, and contextual advertising.
Another technique used by developers and companies is tracking users across multiple sites. This is accomplished by using cookies. In the Vox video, the producer explains how cookies and other tracking tools essentially allow companies to precisely follow a user’s activity across the internet. In other words, it tracks metadata, such as time spent on a page, searches, and cursor movements, and shares it with advertising networks. This allows your data to be matched with certain ads that are stored in a 3-party ad server and push highly personalized advertisements (Stokes 2013).
As technology advances and becomes more accessible, online advertisements are increasingly personalized, which raises privacy concerns. Many users are unaware of these online manipulative techniques that major tech companies such as Google and Facebook have (Vox). As of now, they hold a monopoly over the online advertising industry. Even a simple ad that appears on the screen after a click is generated through countless algorithms.
For this class, I was wondering how artificial intelligence can maybe play a role in online advertising in the future. What if there were no need for the main types of advertisements (display, behavior, etc.)? Instead, an AI model creates a personalized one and links the user to the website platform afterwards. Would it finally be able to knock Google and Facebook off the throne? Would there be a way of controlling it?

## Reading Responses 2 out of 5
### Mar 24 - Manipulated
[Google Doc](https://docs.google.com/document/d/1ofmm_tOJwvCnsp44Tn5Vf8sRVU7vN3y0oevH8oUMxNg/edit?usp=sharing)
Online reviews, ratings, rankings, and comments are often seen as reliable sources of information that indicate that a service or product is high quality. However, these reviews are often manipulated in discreet ways and are not visible to the general public, “Truth is often being overtaken by fakery and manipulation”(Reagle, 2015). In many cases, the public trusts these reviews and often finds out to be disappointed in the end.
The most common method of this type of manipulation would be the creation of fake reviews. Many companies, big or small, have deliberately created fake reviews that give them thousands of five-star reviews. Thus, artificially boost their score online. This could be done through a paid subscription to a third party, paying for reviews, or creating a review bot (Fowler, 2023). Ultimately, the reviews that indicate a product or service’s quality are far from reality, as there are no proper ways to fact-check them, leaving consumers disappointed or business owners overwhelmed.
Another way that reviews are manipulated is through the organization and display methods on online platforms. For example, sites like Google Reviews automatically place the top reviews closer to the top and leave the worst reviews on the bottom, which makes it harder for people to see. This is true for many sites such as Yelp, OpenTable, Amazon, and more. A famous researcher observed that, “some reviews are shown by default and included in the overall star rating while others are shunted to the 'filtered reviews' section” (Reagle, 2015). In other words, platforms allow businesses to actively control certain opinions the public has about them.
Due to these manipulations, it becomes increasingly difficult to fully trust any online reviews, ratings, rankings, and comments. It is common to see businesses post reviews that are sponsored by themselves, place them at the top, and post blogs about themselves. From personal experience, there have been banners on Amazon that say “Best Seller” with many inflated reviews and have an overall high average rating. To avoid this, the best way to find reliable products with honest reviews is to view sources with unbiased/unsponsored reviews that have feedback that is a mix of both positive and negative opinions. Online reviews are useful tools that can help an individual to gain quick opinions about a product. However, there is no way to verify the credibility of the reviews. In these two articles, both authors suggest that it is best to approach reviews with skepticism and awareness of business owners' and developers' tactics.

## Reading Responses 3 out of 5
### Mar 27 - Bemused
[Google Doc](https://docs.google.com/document/d/1bm7X61G1kZ3luj5A3-dg-rOVxZbCZvsJgb6h7YrJnHU/edit?usp=sharing)
Online comments can be viewed both negatively and positively. Negative comments dominate the online environment as they are part of heated arguments and discussions on social media platforms such as Twitter, Facebook, and other sites. However, in the book Reading the Comments by Joseph Reagle, he proposed a different approach to these online comment sections, viewing them as opportunities to gather information, generate curiosity, confusion, and humor. In other words, he described these sections as “bemused.”
As the text highlights, not all comment sections on platforms are interested in spreading misinformation or arguing with others. Instead, users react in ways that demonstrate their playful engagement with the content or bemusement. These responses are “slap-dash, confusing, amusing, revealing and weird” (Reagle, 2015). This quote further reinforces the idea of “bemused” behavior on the internet. This could be broken down into components. The “slap-dash” behavior reflects the natural behavior of humans as they respond to the content. The critic about these comments is that they are very “in the moment.” In class, we discussed how human behavior might change in a given moment. This applies to comments, as they are created in response to a context. However, it is extremely important to recognize that the context is relevant in the moment and loses its relevance as it travels to other platforms.
Comment sections are areas where individuals can interpret information and respond in real time. A more extreme version of this would be live streaming on platforms such as Youtube Twitch, Kick, and more. The streamer is flooded with real-time comments that could range from negative to positive. Applying the “slap-dash” behavior, users react to current information in forms of comments that are written without reflection, which varies from harmful to positive. Comments that were made during this time could be easily misinterpreted as they can be manipulated and put out of place where the context was not similar (Reagle, 2015). Understanding and evaluating online comments is a difficult task because context is misaligned or lost in translation as they cross different platforms. The more people who join the conversation, the more the original meaning/context of the thread loses significance and becomes confusing. Should these online platforms take more responsibility for highlighting the original thread to avoid confusion and misunderstandings that lead to further discourses? Finally, if all comments are often bemused, what's the best way to approach them? Less seriously or not trusting at all?