# Reading Responses (Set 2)
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Checklist for a good reading response of 250-350 words
- Begin with a punchy start.
- Mention specific ideas, details, and examples from the text and earlier classes.
- Offer something novel that you can offer towards class participation.
- Check for writing for clarity, concision, cohesion, and coherence.
- Send to professor with “hackmd” in the subject, with URL of this page and markdown of today’s response.

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## **Reading Responses 5 out of 5**

### March 26 - *Breakup*

Social media adds new layers of complexity to breaking up. In many cases, it prevents the awkward, uncomfortable, and emotional in-person interaction that most people dread: since one doesn’t get to see the other person being sad or angry, it makes it less difficult to break up with them. If the breakup is via text, it also allows the sender to craft well-thought-out responses, as they can go back and re-read the message before it is sent to ensure that the receiver gets it exactly how it is intended. In effect, while breaking up over text is frowned upon by most teens, a considerable number of teens with relationship experience have broken up with, or been broken up by, someone via social media or text (Lenhart et. al, 2015).

On the other hand, there are certain disadvantages to breaking up via online platforms. For instance, it changes the relationship from being completely private to completely public, given the amplifying nature of online digital spaces. Social media platforms like Instagram and Twitter become outlets where people can publicly express their feelings and emotions, specifically through posts and tweets. For instance, many people rely on posting new pictures to announce a relationship, and so, erasing such pictures can therefore serve to announce a breakup. Users can also use social media to send indirect messages known as “second-order” messages. As further described in Chapter 4 of Gershon's piece, *The Breakup 2.0*, sharing cryptic tweets, the lyrics of a song, and even quotes can be used by someone to consciously imply that the feelings expressed by the words are their feelings, as well (Gershon, 125).
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### March 30 - *Shaped*
How many people commented on the picture you posted today? Although it is intrinsic in our nature as human beings to seek for recognition, it seems likes and comments have become the ultimate sources of self-validation. In today’s digital and interconnected world, it is so easy to get wrapped up in the successes and the lives that other people showcase on social media, prompting users to engage in social comparisons and share so much about themselves to get the approval of their online “friends”. As described in Reagle’s (2014) chapter “Shaped: Aw Shit, I Have to Update My Twitter”, web interactions, such as the liking of a photo, “have come to define how people see themselves”- more specifically, as reflections of their own edits and the comments of other people. This has caused a cycle of “self-promotion and envy” on already “envy-ridden” platforms, as users engage in a never-ending race to share who is living the best life and having the most fun.

Effectively, social media is a very toxic mirror, where users can control and alter images of themselves to boost their self-esteem and sense of social gratification. Nonetheless, this sense of self-esteem is momentary, as obsessing over their relative standing to other people might lead users to experience a diminishing sense of their own well-being, causing them to feel worse. Furthermore, this unhealthy self-obsession has been shown to support the rise of narcissist personalities among users, as they attempt to support their senses of self through continuous external self-affirmation. So, although the consequences of the internet vary greatly between each user, it is evident that others' comments and likes on social media can greatly affect us.
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### April 6 - *Algorithmic discrimination*
The web is far from neutral. Whether it is our news feed on Facebook, our “For You” page on TikTok, or our ‘Top Picks’ movie list on Netflix, the data on websites is usually crafted by online algorithms.

These algorithmic systems collect our browsing behavior to develop personalized and engaging user experiences. They can also appear in real-life circumstances, increasing the price for vehicles on Lyft when demand is high, or predicting a student’s final grade based on previous assignment scores ([Wilson, 2020](https://personalization.ccs.neu.edu/)). In effect, online personalization stems from the plethora of data we leave behind, which then prompts the creation of reputation silos by advertisers to better manipulate content.

Although algorithmic personalization is generally beneficial to users, it can also be harmful, used to users’ disadvantage through price steering and price discrimination. As reported in studies conducted by Hannak, Soeller, Lazer, Mislove and Wilson, many users experience price inconsistencies and discrimination across multiple sites ([Hannak, Soeller, Lazer, Mislove & Wilson, 2014](https://personalization.ccs.neu.edu/Projects/PriceDiscrimination/)). For instance, the travel site [Travelocity](https://www.travelocity.com/) provides members with lower prices than non-members, on the same hotels. Travelocity also alters search results for users browsing from iOS devices, and consequently administers price discrimination against users browsing from Chrome on Android, Safari, and other desktop browsers (Hannak, Soeller, Lazer, Mislove & Wilson, 2014). Many other internet users have also noticed strong racial bias and discrimination in Google's search results. For example, when one woman searched Google images for "unprofessional hairstyles for work", the result yielded black women with their natural hair, while the opposite yielded images of white women ([Rutherford & White, 2016](https://www.buzzfeed.com/fionarutherford/heres-why-some-people-think-googles-results-are-racist)).

Personalized algorithms shape our online lives and filter the data we see into content we find palatable and engaging. In essence, it is important for us as users to understand how these algorithms work, as well as the data they use and their potential to inflict harmful consequences in unintentional ways.
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### April 12 - *Gendered Work*
Social media and the internet have redefined gendered work. Although gender inequality continues to be present in various aspects of the workplace, the ability to work remotely has provided many opportunities for women in business. For instance, activities like blogging and craft-micro enterprises have propagated a rise in female entrepreneurship over recent years (Duffy & Pruchniewska, 2017). The ability to earn money has never been easier, and more women have turned to social media to launch their brands and businesses: not only do sites like Instagram provide them with income, but they also offer women “flexibility and outlets for their creative passions” (Duffy & Pruchniewska, 2017).

In contrast, more men have taken the more supportive job of Instagram husbands, helping their partners take, “staged photos of themselves for their Instagram account” ([James Cave, 2017](https://www.huffpost.com/entry/instagram-husband-tips_n_57db0afae4b0071a6e0620c9)). Through these pictures, bloggers can engage in **soft self-promotion**, branding themselves in ways that are “non-invasive” and subtle. They can also feature sponsored content, which allows them to monetize their good taste and make their brands seem more established ([Taylor Lorenz, 2018](https://www.theatlantic.com/technology/archive/2018/12/influencers-are-faking-brand-deals/578401/)).

This new economy appears to be gender-neutral, where the rise from independent work can be framed as, “a movement away from bureaucratic, male-dominated work structures” (Duffy & Pruchniewska, 2017). Although this utopian rhetoric suggests that, “men and women have a level playing field”, it is important to acknowledge that gender inequality still exists, especially in media and creative industries. In essence, this new technological age poses many changes for both men and women, and gendered divisions in cultural work will still be maintained if we fail to account for them.
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### April 16 - *Bemused*
Comments have become a new genre of communication. Usually found on the bottom half of the web, they are reactive, short, and asynchronous and can range all the way from providing feedback to asserting negativity and hate. Sites that “treat their users as community members tend to have better comments”, however, after a network of people becomes popular, people want to bring their friends ([Reagle, 2019](https://readingthecomments.mitpress.mit.edu/pub/dtys4tyk/release/2)). Thus, networks can rapidly become overly populated by “jerks, spammers and ads” and a target for those “who wish to exploit it via spam and manipulation”, losing intimacy and serendipity, as well ([Reagle, 2019](https://readingthecomments.mitpress.mit.edu/pub/dtys4tyk/release/2)).

There are multiple things that sites can do in order to make their comment systems more resistant to abuse. For instance, social media sites like Twitter have developed filters that allow users to block or label others as spammers. Similarly, the site Slashdot allows its users to filter comments based on other’s ratings of “fair or unfair”, and Facebook and Google have required users to use their real names ([Reagle, 2019](https://readingthecomments.mitpress.mit.edu/pub/dtys4tyk/release/2)). In effect, relatively simple approaches like these can do the trick, helping create more prosperous and civic cultures online and limit the number of trolls, bully battles and misogyny.

In essence, readers are often advised to not read the comments, as sifting through them can provide so much information about ourselves and ways that “other people seek to exploit the value of our social selves” ([Reagle, 2019](https://readingthecomments.mitpress.mit.edu/pub/dtys4tyk/release/2)). However, it is important to be able to read online comments and respond to them in “technical and communal levels”, instead of just avoiding them.