###### tags: `CDA`
# Reading Responses (Set 2)

### March 20 Friday - Ads & social graph background

#### Crumbs That Follow You
When accessing the internet, users often find themselves being followed by what they would usually consider to be a sweet dessert. Cookies are always following you, curating your online experience and also following you through the different advertisements pop up in your way. At first, this can feel convenient, as the content and ads you see seem more relevant to your interests, but it also raises questions about how much of your activity is actually being tracked behind the scenes. The Stokes reading helps explain how these different advertisements are perfectly structured to appear frequently across the internet in numerous different shapes and sizes. As Stokes explains, “online advertising… encompasses display adverts found on websites, adverts on search engine results pages… adverts placed in emails and on social networks.” This widespread nature of ads is due to companies tracking all of a user’s input, engagement, and conversations across all platforms. This level of tracking is what allows ads to feel so personalized, but it also highlights how closely user behavior is being monitored in order to make these systems work.

The Vox video highlights the nature in which cookies track a user's engagement. Cookies serve as some form of a running list describing each piece of information that could be stored on a site. This list of information is unique to each individual user. Cookies originally were designed to improve web functionality; however, they have evolved to track users across web sites with third-party cookies, creating some sort of a multi-dimensional tracking web. This allows companies like Google and Facebook to build detailed profiles of users, which are then used to deliver highly personalized advertisements. This becomes concerning when considering that users often don’t fully comprehend the scope of what information is tracked. Overall the two articles highlight the pros of having a personalized internet experience, but they also outline the concerns behind how much control users carry over their information. If users are largely unaware of how their data is being tracked and used, should companies be allowed to continue this level of personalization without stronger transparency or regulation?

### Mar 24 Tuesday - Manipulated

#### FIVE Stars but ZERO Trust

Before making a decision online, many people say to always look at the reviews. What happens when all the reviews say five stars, and you are left with a subtier product asking yourself how this deserves five stars. Experiences like this highlight a larger issue with how online reviews are created and trusted. Reagle explains that online reviews were originally created to solve the issue of information asymmetry, where consumers do not know the true quality of a product before purchasing it. With its original intent in mind, reviews should be a win-win situation with the product gaining more customers, and future buyers being able to see real customer feedback on the product. However, this system has become increasingly unreliable as manipulation has become more common. As Reagle notes, user reviews were meant to help “let truth loose” in the marketplace, allowing honest opinions to guide consumer decisions.

Fake reviews are starting to spread more rapidly. For example, the other day I was hanging out with an upperclassman friend, and he told me about how he was flooding a bad professor’s reviews with 5 star reviews on RateMyProfessor to discourage people from registering for the section with the professor he wanted. This issue becomes even more serious in the Seattle Times article, which explains how fake reviews are now being addressed at a legal level. As the article explains, “the rule prohibits businesses from buying or selling fake reviews or testimonials,” showing that these practices are now being recognized not just as unethical, but as illegal. This growing spread of misinformation makes it harder to separate real experiences from fabricated ones—so how can consumers confidently make decisions in a system built on trust that no longer feels reliable?

### Mar 27 Friday - Bemused
#### The Three Wolf Effect

When navigating online spaces, there are numerous occasions where certain details will seem “off”, and you aren’t able to point out exactly what’s wrong. More times than not, the opinions you formulate when reading articles or reviews, are almost predetermined by what you see first—whether it’s the earliest comments, the way information is presented, or the tone that is already set before you even engage with the content. This idea is detailed in Chapter 7 of Joseph Reagle’s “Reading the Comments”, where he details the concept of bemusement. In the chapter, there is a graph that perfectly summarizes the relevance of how social media engagement works, favoring quantity and speed over quality. The bar graph shows the price difference between a professionally developed ad campaign versus a comment based one, highlighting the ease and inexpensiveness while still outputting similar results.

This confusion is also found on multiple rating based services. Multiple product reviews have led to products blowing up and peaking on the Amazon top 100 because other customers found the reviews to be entertaining. For example, Reagle, details the story of the three wolf shirts and how a review about the pros and cons of said shirt led to insane levels of success. However in order to properly rate something, you must fully comprehend the rating system itself, and Reagle breaks down the confusion behind rating systems. I related this rating system breakdown to similar experiences in my hometown friend group, where we were convinced that a proper rating skill was based on a more global level, making most of our ratings on various products not breaking the 5 or 6 marks out of 10 score.

Reagle also connects this to ideas like implicit association tests. Just like with early comments or ratings, people assume they are making independent judgments, when in reality those judgments are influenced by factors they cannot fully see. Overall, these examples show that what feels like personal judgment online is often shaped by hidden structures we barely notice, which leads me to wonder the extent to which our opinions are actually our own, and how much are they influenced before we even realize it?