DIG 210 Group 3 Observers: Political Bias & Trust in the News

Bias

 

 

 

TrustNews

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The reason we collected this data was to understand how exactly our class was segmented, based on political bias, news source preference, and trust for traditional news sites. Our intention was to see if there was a possible link between trust for news sources and political bias, since we’ve had good discussions about it in class. To do this we asked 3 questions: 1. How do you get your news? 2. How do you identify politically? 3. Do you trust traditional news/print-news sources?

Our intentions with this last graph was to correlate trust with a value. Trust for traditional news sources was measured as yes, mostly yes, mostly no, and no. Each response was given a value of  1, .5, 0, -.5, 1. Each new trust value was attributed to its  respective political group (x-axis groups), averaged, and then normalized based on their representative parts of the whole. As a whole, those who identify as left leaning trust traditional media (and are the majority of responses), and those who identify as right-leaning (minority of the class) usually trust traditional media less. Those who identified as hating politics tended to trust traditional media sources.

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Group 6 Responders

Group 1 brought up an interesting point about gamification.  They said that people have issues with gamification and figure out ways to treat the system.  This is true but also gamification is a very intuitive way to surveil someone.  As we asked in class many people like to play games whether it is on the phone or computer or whatever other system, the process of gamification makes it seem like the input of your info is trivial.  For instance, put in your birthdate so that you become “old enough” to play a game.  Next it can ask you to make sure you share your location so that you can get location specific notifications or be able to see when you are near your friends. Just like that you are being tracked without really thinking twice about the information you immediately volunteered to the game.  
Group 5 brings up a good point when writing about Wolfram.  They stated that after Wolfram saw all of his data he was able to make both broad and specific changes to his lifestyle and sort of chronologically order his life through his files and emails.  This is an interesting point given group 1’s statement that people do not like to see their data and they cheat it, but what if something was tracked inadvertently? The “cheating” they were referring too could have been minimal as not everyone is equally as likely to manipulate their data to their liking. Could seeing mass amounts of specific personal information both be interesting and informative? Could it also pose specific problems?

Responders DIG 210

In class earlier this week, we believe that the number of self reported gamers was surprisingly low compared expectations. As a result, we feel there is importance in further exploring our personal experiences with games compared and contrasted to gamified life outside of our consoles and PCs. A key aspect of each we feel is important is the borderline compulsive need to level up or collect achievements.

Each of us in group 2 have at one point found ourselves laboring through a console game that’s gameplay has long since ceased bringing joy. We were working for nothing other than leveling up. The goal we were chasing significantly outweighed the tedium of playing through missions over and over again.

When we began using fitness trackers for the first time, many of us were struck by the shocking parallels in our motivations to collect achievements and level up in fitness and video games. As mentioned in class, we even found ourselves focusing an alarming amount of effort on cheating the system to achieve our goals through loopholes as much as the intended tasks. As Whitson and our class concluded, the simple pleasure of meaningless praise and badges is enough to strongly shape our behaviors.

Observers Group 6

This data returns the results we would generally expect. Knowing that about 25% of the Davidson student body are student athletes, our sample (classmates) of this population is representative of such a percentage, with 28% reporting themselves as athletes. Additionally, it is not surprising that such a high percentage of people were athletes in high school, as many high schools would require you to be on teams as a physical education requirement. It also makes sense that the majority of high school athletes exercise daily in college. Usually high school athletes are used to being active every day with practice after school. Because they are no longer on a team, it makes sense that they want to keep up this consistent exercise and are used to blocking off a certain amount of time in their day for exercise.  It reinforces the idea that humans tend to fall into routines and habits, and once these habits are established, they are unlikely to be broken.

Even when transitioning from high school to college, exercise habits seem to be so strongly ingrained in humans that we stick to them even through big life changes like moving into a new place and settling into college life. It is also interesting however that with the last poll we took with the amount of work that students do throughout the week the large majority work out at least 3 times a week. Working out is also seen by many to be a good way to clear the mind as well as blowing off steam. There is an obvious correlation between high-school athletes and the amount they workout every week.  It would also be interesting to see what many people would consider to be working out since “working out” can take many forms from playing a sport or lifting to going to a class like cardio dance or even intensive sessions of yoga.

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Data Culture Group 1- Readers

In “Gaming the Quantified Self,” Whitson says, “I want to suggest two things: 1) that gamification is a form of surveillance; and 2) this surveillance is pleasurable.”  Yes, gamification is definitely a form of surveillance, but this type of surveillance is not pleasurable to everyone. We know countless people who have had negative experiences with personal tracking methods such as sleep tracking.  Along the same lines, Whitson also says that “When we subject ourselves to this quantification, we come to know and master the self.”  As we have discussed in class, rather than becoming a master of self, quantifying oneself leads to individual corruption, and people learn how to cheat their different tracking methods.  Oftentimes, people figure out what they need to do to cheat the system and come up with the outcome that they want to see instead of what would be most beneficiary.  Whitson’s thoughts, while well founded, are far too idealistic.

In “The Personal Analytics of My Life,” Wolfram mentions that all of the personal information that an individual gathers is “going to give us a whole new dimension on experiencing our lives.”  However, after reading this specific article, it is unclear how.  All of the data that Wolfram has collected allows him to make sense about his everyday life in the past, but how is knowing at what time he has taken phone calls or how often he has received emails going to influence his future? That is not to say that the data we collect today through gamification will not help us in our future, as data collection has significantly changed throughout the years.

 

DIG 210 – Readers – Group 5 – Week 11

Stephen Wolfram dissects his personal email, keystroke and phone data spanning an entire decade. From 2002 to 2012, he logged his daily usage of almost all technological functions that he uses. This data spans the course of an era which saw an exponential increase in the use of personal technology as well as in innovation. The changes in this time period are reflected in the increases seen across multiple graphs Wolfram includes in his blog article, particularly his outgoing emails, events per day and hours spent on his phone. However, the graph on daily keystrokes is the one outlier; Wolfram’s keystrokes per day decreases over time.

Early on in the post, Wolfram brings up the “self awareness” he has built by collecting all of this personal data. Although documenting all of these different things may have made him more conscious of his actions, I think it also exemplifies the “busy bee” work ethic that so many more workers have begun to embody over the past two decades, with the rise of computers, emailing and IM. Today, we are constantly responding, typing and searching. I was almost shocked by the fact that he has sent a “third of a million emails [he’s] sent since 1989” and has more than 1.7 million files.

After reflecting on all these visualisations of his personal data, Wolfram could make some both small and broad changes to his work habits/ethics and lifestyle that would greatly increase his work efficiency and quality.

Surveillance is not only practiced through listening to your phone calls or reading your emails, it is also part of our everyday digital user experience, according to Whitson. With the help of gamified applications that are both aesthetically pleasing and, in the long run, intimately satisfying, all sorts of companies attempt to lure us into giving up personal information voluntarily. The pleasures of play, the promise of a ‘game’, and the desire to level up and win are used to inculcate desirable skill sets and behaviours. The real-time feedback about user’s actions amasses a large quantity of most personal data, which in turn can be used to forecast a consumer’s behavior. And for some reason we all love to be surveilled in this way.

Whitson argues that this pleasurable surveillance relies on three conditions that are provided by gamification: willing participants, diversification and trust in the underlying algorithm. With the help of these attributes, gamified digital applications are able to transform our intuitions, ambitions and even feelings into something more reliably and seemingly objective – a stream of numbers. Even though this data provides us as a consumer with more suitable and personal options, I believe that giving up your personal information voluntarily makes you a player in a game that you never really agreed to; and I am not even sure if there is a way of winning it.

In Sam Levigne’s article, “Taxonomy of Humans According to Twitter”, he describes the process one can use to peg twitter users into different categories as it appeals to consumption.  According to Levigne, everyone has access to this data on-boarding and can use it to make ads on twitter.  Essentially, the process can categorize twitter users, based on their activity on the site, into countless different groups.  The individual making the ad has liberty to target just about any audience imaginable.  This goes to show that everything we do online can be tracked and can place us in categories that we may or may not have necessarily associated ourselves with.