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# Reading Responses (Set 2)
- Checklist for a [good reading response](https://reagle.org/joseph/zwiki/Teaching/Best_Practices/Learning/Writing_Responses.html) of 250-350 words
- [ ] Mention specific ideas, details, and examples from the text and earlier classes.
- [ ] Offer something novel that you can offer towards class participation.
- [ ] Begin with a punchy start.
- [ ] Send to professor with "cda-r" in the subject, with URL of this page and markdown of today's response.
## Reading Responses: 5 out of 5
## Friday October 26: Online Advertising
Ads are everywhere online, and according to Robe Stokes, “digital advertising can reach customers anywhere where they can access the web” (2014). Advertisers use online ads to increase their immediate sales, raise brand awareness, and increase their impact in various marketplaces. These ads are meant to inform, persuade, and remind consumers about products. To make an ad available on a website, advertisers have to purchase a space, then fill the space with static or interactive content to encourage users to engage. In addition to websites, advertisements are found on social media, maps, and applications. 3rd party advertisements set a cookie when an impression is made on an ad, and can track data after the ad has been viewed or clicked.
Advertising servers and networks provide advertisers with data about interactions with their advertisements as well as different targeting techniques (location, network type, behavior, cookies, IP address) to determine the best market for the ads. These networks can also allow advertisers to purchase ad space on channels rather than individual webpages, providing more places specific ads can be seen.
I saw so many ads on the internet that I actually installed an adblocker. I spend a lot of time on my laptop doing homework and academic activities, that I got distracted by ads and ended up procrastinating. Now, I don’t see any ads on my laptop. On my phone, I still get ads. Specific ads, like floating ads, interstitial banners, and popups make using apps and reading stories a little difficult, since they block what I was trying to do on my phone, but banners are fairly easy to ignore. I do not appreciate that social media apps like Instagram and Facebook take my recent browser history and provide advertisements for websites I’ve visited. It feels as if the apps are breaching a privacy boundary. I wonder how the internet would change, especially with the net neutrality issues, if all advertisements were blocked? Would access to individual websites come at a cost? Or would all internet access still be free?
## Tuesday October 30: Manipulated
Fake comments and reviews are plentiful on the internet, monetized in a way that “extrinsic motivations crowd out intrinsic ones” (Reagle, 2015, 71). Online reviews for products, restaurants, services, and anything available for consumer use are one way that people can judge how to spend their money. However, these reviews can’t always be trusted. Companies and businesses will pay people to give their product a positive review, or pay to take down negative comments. In addition, people who post negative reviews will ask for some kind of compensation to change their review. Since money is usually involved in these transactions, the nature of the review changes. The initial idea to write a review to help out other people is overcome by the money offerings, so people will review products they never purchased or tried to get more money. Sellers themselves will even comment their own product reviews to raise their overall rating if there are too many negative comments.
I use reviews to buy products online very often. I buy a lot of clothes online, and I like to see what other people say about them before I purchase the clothing. I have found that many of the comments have high star values, while there may be a slight complaint in the text of the review. It is very hard to tell if these reviews are genuine or faked. Typically, I only look at reviews with pictures because then I can tell if someone actually purchased the product and I can see what it actually looks like. When it comes to restaurants, I have found that online reviews are not very helpful because I only find negative reviews for all restaurants, making the reviews fairly useless, and I usually end up judging the place on the menu and pictures of the inside. There is no easy way to tell if a review is manipulated or sincere based on superficial searching. I wonder how online searching for products and services would change if large review providing services (yelp, amazon, and many more) removed scaled rating systems and only contained comments? Would there be more genuine reviews?
## Tuesday November 6: Dating
People lie on the internet, making “the best representation of themselves,” which is not always their real selves (OKTrends, 2010). In most cases, this is harmless. But with online dating, misrepresentation can be harmful. According to the OkCupid trends, the majority of people claim they are two inches taller and make 20% more money than they do in reality. Men exaggerate a little more than women, but it’s all in the name of getting more responses.
When looking at response rates, biases majorly affect the messaging behavior of everyone. Overall, blacks received fewer responses and white people responded the least to everyone, but were more likely to respond to other whites than any other race. These racial biases emerged completely from the users themselves, not the OkCupid algorithm, as the match rates were about equal for all races.
Chris McKinlay was able to take advantage of the algorithms to find his wife, creating a database that had the most popular questions and answers from OkCupid. He was able to make a profile that answered questions sincerely, using the algorithm to determine the importance, and found thousands of women that were 90% or higher match rates. However, when he actually went on dates with these women, the compatibility was often not there. After 88 dates, he found the woman he wanted to marry.
Digital communication has vastly changed the dating landscape. There are now algorithms and computer programs that can determine how much you are going to like someone based on simple multiple choice questions. However, these algorithms are not completely accurate, based on everyone’s lies on the internet. McKinlay found that he was not compatible with most of his dates, likely because he was insincere in the importance of questions on his profile, and the women were insincere in their profiles as well. He was able to engineer the optimal profile, which was not a complete reflection of himself, causing many of his dates to fail. However, he was also failing when sincere in his answers. This leads to the question, would online dating algorithms be more accurate if everyone was completely honest in their profiles? Or would there be more people finding very few matches, with an overall low compatibility?
## Friday November 9: Breakup
Breaking up over the internet is one way to end a relationship, and Ilana Gherson mentioned that breakups can often occur from “interpretations of words” that were posted online (2010). In this chapter of her book, Gherson outlined how many couples broke up over the internet, using away messages in IM and Facebook statuses. With the away messages, people expressed their feelings through song lyrics and quotes. Women often used these quotes to show how strong they are after the relationship ended, even if they were incredibly heartbroken. On Facebook, people would change their relationship status depending on whether or not they are in a relationship. Based on external opinions, couples would decide to say they were in a relationship on Facebook or remove the status altogether. As the relationship declined, people would post fake statuses, like they got married to their best friend, or change the status to single or “it’s complicated.” Because everyone has their own opinions on how to use Facebook relationship statuses, the information they provide about relationships can be hard to comprehend.
I don’t use Facebook myself, but I have found that Twitter and Instagram are used in similar ways to the away messages of IM. On Twitter, people often subtweet each other with song lyrics, quotes, or messages directed at a person. These messages can be pretty easy to decode depending on how well you know the person. As relationships start to end, people start to subtweet each other on social media, and these interactions can be seen by many people. On Instagram, people going through breakups will delete all their pictures of each other. Even if you are unaware of the decline of the relationship, Instagram posts and captions are huge signs that something changed in a relationship. I wonder if the trends associated with people posting quotes after a breakup will continue as social media platforms change. Will people continue posting quotes for everyone to see? Or will they just tell their immediate friends?
## Tuesday November 13: Algorithmic Discrimination
Google itself may not be racist, but the search results project “wider societal biases that are brought into relief by the algorithm,” according to Rutherford and White at Buzzfeed (2016). The search results for images in google are primarily white people, and when you search for a person or body part that is not white, the results are fetishized, sexualized, or racist. Autosuggestion itself is slightly racist because of the mass search habits of users. Meta-tagging and context around images can also lead to racist results because Google is not always accurate in their search results.
In e-commerce, personalization can cause different people to see different results. Based on browser, mobile phone, desktop, location, previous searches and purchases, and more, websites can pick and choose what kind of data to present on a search. AMT users specifically experience personalization across many sites.
The bias created in e-commerce personalization may not be inherently racist, but can cause racial problems. For example, android users receive higher priced items in their searches on personalized websites. This creates a divide between android users and iPhone users that could appear racial in certain populations. Travel sites in particular could create many problems from personalization. If one race gets consistently lower priced hotels than another race, the algorithms they use could be considered racist. I do not believe the algorithms on these websites are meant to be racist, but I feel that the search results are biased to certain groups of people based on their material goods. I wonder if companies will change search personalization to remove social biases in the future.