Question Popularity

This week I was interested in looking at which questions would be most popular in the google docs using word count as a measure of popularity. My first hypothesis was that the first questions would have the most words because they are the ones that people first see. My other hypothesis was that questions dealing with issues that occur in the earlier parts of the book would be more popular because perhaps people hadn’t read all the way to page 200.

Question Group 1 Words Group 2 Words
1 571 883
2 517 430
3 744 625
4 470 503
5 388 349
6 460 443

Dig 210 Blog Post

The table and graph show that there were similar tendencies between the groups but no clear patterns for explanation. Question 3 references page 182 yet was one of the most popular questions so my second hypothesis seems to be disproved and while there is a gradual decrease from the first question to the last one it is not significant enough to prove my first hypothesis. Thus, it could be that certain questions were just more popular and easy to answer than others.

The Cost of Perfect Dataveillance

For most of the semester, I have typically argued that society’s constantly improving ability to monitor and record data about our daily actions would be beneficial, provided that the information would be more or less equally accessible to everyone.  For example, if car insurance companies had perfect information available to them to evaluate how risky drivers are to insure, they could naturally develop a socially optimal pricing structure (in addition to creating incentives for people to be safer drivers).  However, what I read from pages 101-205 in the Circle began to make me question that assumption.

If we view the Circle as a closed network in which everyone who works for the Circle has more or less perfect access to their electronic information about one another, we begin to see some of the potential problems that could arise in this society with perfect access to information.  One of the biggest problems that arises in this scenario is the fact that the can be large transaction costs associated with collecting the information.  If the opportunity cost of Mae filling out various social media profiles (the revenue she could have generated for the company if she had been working in Customer Experience for the time it took her to fill out the profile) exceeds the “Community Value” that The Circle gets from having this additional information, then obtaining this information was not efficient for the company.

In addition to this, The Circle also creates an adverse incentive for people to use social media to inefficient levels.  The Circle may value the data it obtains very highly, but if the data was created for the sake of creating data (for example, people trying to climb up the popularity rankings), there is no guarantee that the data is accurate and/or useful.  For example, when Mae is doing her best to race to the top of the popularity rankings, the book mentions that she commented 33 times on a single page.  From the context given, it seems fairly safe to assume that her comments were made solely for boosting her ranking, and not because they reflected her actual opinions.  Therefore, returning to the issues of transaction costs that perfect dataveillance could potentially incur, it seems as though The Circle would have been better off if Mae had been working in Customer Experience than commenting on that random page.  The value of these comments ties back in to our previous discussions about what types of communication are considered “good” communication.

One of the best examples of this in The Circle is the concept of “Zinging” someone.  When someone receives 10 “Great Job” Zings for completing a relatively menial task, it’s ultimately a waste of time from the people who sent the Zings.  This wasted time is ultimately the largest cost that was created when The Circle implemented the popularity rankings.

The common theme that ties the past three paragraphs together is that perfect dataveillance is inefficient, because the additional benefit of having access to 100% of information instead of 99.9% is relatively small, but the costs of obtaining that extra 0.1% is relatively high.  While this does not entirely refute the position that I initially believed, that perfect dataveillance is not detrimental to society provided that is it not applied asymmetrically, it definitely reinforces the fact that we should not attempt to achieve perfect dataveillance purely for the sake of perfect dataveillance.

Observations: Eye contact with Dr. Sample by table

Tuesday March 31

Table 1 Table 2 Table 3 Table 4 Table 5 Table 6 Table 7 Table 8
1:45 0 0 1 0 0 1 0 1
1:50 0 1 0 2 0 0 0 0
1:55 1 1 0 1 2 0 0 2
2:00 0 2 2 1 1 0 0 0
2:05 0 1 1 2 0 0 2 0
2:10 0 0 0 0 0 0 0 0
2:15 0 0 0 0 0 0 0 1
2:20 1 0 0 0 0 0 0 0
2:25 1 0 1 0 0 0 0 0
2:30 0 0 0 0 0 0 0 0
2:40 0 0 0 0 0 0 0 0
2:45 0 0 0 0 0 0 0 0
2:50 2 0 0 0 0 0 0 0
Total 5 5 5 6 3 1 2 4


Thursday April 1

Table 1 Table 2 Table 3 Table 4 Table 5 Table 6 Table 7 Table 8
1:45 0 2 0 0 0 0 0 0
1:50 0 0 0 0 0 0 0 0
1:55 2 0 3 0 3 1 0 0
2:00 1 1 0 2 1 0 0 0
2:05 0 0 0 0 0 1 0 0
2:10 1 0 1 0 0 0 2 1
2:15 0 0 0 0 0 0 1 1
2:20 0 1 0 0 0 0 1 0
2:25 3 2 2 1 1 2 3 4
2:30 1 1 2 0 2 0 0 0
2:40 0 0 0 0 0 0 0 0
2:45 0 0 0 0 0 0 0 0
2:50 0 0 0 0 0 0 0 0
Total 8 7 8 3 7 4 7 6

For my observations I separated the tables into groups and measured how many students at each table were making eye contact with Dr. Sample at 5 minute intervals. The Table Guide shows what number correlates to each table in the classroom. The purpose of these observations was to measure attentiveness to Dr. Sample and the lecture. I should have recorded more intervals if I wanted to get a true reading on which table pays the most attention to Dr. Sample because recording every five minutes does not provide enough data. In addition this is a flawed methodology because I am measuring attentiveness based on eye contact, so this method assumes that if you aren’t making eye contact than you are not paying attention to the lecture, which isn’t necessarily true. From the observations, I can’t reach any substantial conclusions on which table focused the most and least on the lectures of March 31 and April 1.







How long are we lectured?

For my data collection this week, I decided to time how long Dr. Sample talks for each class. I collected this data using my phone, and every time Dr. Sample paused (asking a question, writing on the board, etc.) I hit the split button. Then every time one of us spoke, I completely stopped the clock and would start it back up when Dr. Sample started talking again. Here are the results:

Tuesday —    43 minutes 12.45 seconds of talking for Dr. Sample

4 minutes 34.03 seconds of “dead” periods

27 minutes 13.52 seconds of students talking

Thursday —  26 minutes 20.21 seconds of talking for Dr. Sample

1 minute 59.86 seconds of “dead” periods

46 minutes 39.93 seconds of students talking


It is obvious that Dr. Sample likes students to be engaged and part of class. He also does not like periods of silence over 10 seconds (that was the highest “dead” period where he wasn’t writing on the board or pulling something up on the computer).


Social Norms and the Internet

When looking at Joyce Walker’s “Narratives in the database: Memorializing September 11th online,” I was especially struck by the same quote as Chris. It reads as follows:

“The space of the Internet, with its connective elements of database, hierarchy, and hyperlinking, is nevertheless constrained by the categories we create and into which we place its discrete elements,” (Walker, 139).

I find the relationship between social norms and activity on the internet particularly interesting, especially with the creation of anonymous apps like Yik Yak. I would agree that for the most part people’s activity on the internet is bound by social norms. You don’t very often see people post extremely controversial things on public domains such as Facebook or Twitter. When I read this quote I immediately thought of Yik Yak and the controversial things that are posted every day. The key here is the anonymity associated with Yik Yak. If you post something controversial on Facebook people will connect you to your beliefs. On the other hand, there is no way of tracing a particular Yik Yak to a specific person so there is a sense that there are no consequences associated with “yakking” whatever comes to mind.

I then thought about how most of the outwardly inappropriate or hateful yaks get taken down soon after they are posted. Each person in the Yik Yak network has the power to influence what content is removed and what stays so in this sense social norms are still enforced on anonymous venues like Yik Yak. When a yak is taken down in a certain area it could be seen as a reflection of the beliefs of that region of yakkers.

Thus, this enforcement of cultural and social values on the internet brings up the question of bias. Are the things you read on the internet really expressing both sides to the story or is the content inhibited by social norms?

Disney: Behind Closed Doors

The Disney MagicBand is an interesting appliance. Rakim’s blog post explains greater research in the band and comes to the conclusion that the “more customized experience” might be worth the personal data breach.

I find it very interesting that on the DisneyWorld site (link below), there is plenty of talk about the MagicBand’s perks, including ease of room entrance, food purchases, and FastPass+ access to a multitude of experiences. But there is absolutely no notice of any of the “behind the scenes” features of the bands, especially Disney’s ability to track your every waking move. With this data, Disney can increase their efficiency, making more profits, while making more people “happy.”

I personally think it is an ingenious strategy and will ultimately do wonders for the amusement park. But I do believe that this trickery is not natural. Personally, the best part about Disney World for me was that everything was unexpected. I never knew what ride, structure, or cartoon characters I was going to see at every turn. It was exciting and incredibly appealing to me in my adolescence. I feel like the band takes away from this experience. It makes actions predictable and ultimately less fun for a couple extra bucks. The data will definitely make the park more efficient, but playing on people’s affinity towards “immediate payoffs,” (Dr. Sample’s Comment) could have consequences that affect the unpredictability of the park and human nature as a whole in the future.


The Emotional Argument

John Foreman’s use of the doom-and-gloom tactic is interesting. On one hand it is a useful narrative that showcases his opinion; suppressed enthusiasm by the consequences of the technology.  But is his negative attitude towards where the technology is pushing society any different than many headlines make? Should I stop drinking milk because it increases my risk of getting cancer? Should you stop reading this blog post on the computer that sits in your lap because it kills sperm count? Should you stop reading my nonsensical words on your phone that is sitting on your chest because it might cause breast cancer? Some of these cases are using worst case scenarios to make you believe whatever fact or opinion they have.

Bringing me to my second point, Foreman is using similar methods that an advertisement will use to push their product/opinion. He is attempting to illicit an emotional response so that his argument becomes more valid in the reader’s mind (the better his argument gets, the better his name is known, the more books he sells). Objectively, are his points valid? Certainly. Does his use of the doom-and-gloom tactic weaken his argument? Definitely not. This is how you win arguments, by presenting facts in a way that illicit an emotional response. Would you be persuaded by a presidential candidate if they just spit out facts, or would it be more effective to give you a sob story to showcase the facts? The answer is pretty clear (for the majority of people). So does using emotion fueled targeted ads destroy humanity? No because at the end of the day, you are making the decision to buy the good or service, and (depending on who you talk to) this ability to freely choose is what makes us human.

The Time Spent Talking Among the Class and Clothes for the Week

Group Table numbering
Group Table numbering

For Data Collection and Observations this week, I tracked and totaled the amount of time spent talking within the class. I tracked the amount of time spent talking by groups and professor Sample along with the amount of collaboration among the group.


29 total in class= 11 long sleeve shirts and 3 pants were worn.

Talking Among the Groups

Professor Sample- 23 mins, 25:58 seconds

Group 1- 1 min, 39:16 seconds

Group 2- 4 mins, 39:30 seconds

Group 3- 1 min, 27:20 seconds

Group 4- 2 mins, 14 seconds

Group 5- 2 mins, 56:13 seconds

Group 6- 1 min, 44:46 seconds

Group 7- 1 min, 35:23 seconds

Group 8- 1 min, 23:42 seconds

Collaboration Among the Groups- 33 mins, 54:52 seconds

Longest streak of groups responding to each other- 9 (when talking about

Professor Sample spoke the most whenever introducing the next part of the lesson for the day. Within the different sections of the lesson, student groups controlled the flow of conversation.


29 total in class= 19 long sleeve shirts and 25 pants were worn.

Talking Among the Groups

Professor Sample- 16 mins, 52:04 seconds

Group 1- 22:01 seconds

Group 5- 8:21 seconds

Group 6- 5:12 seconds

Collaboration among the groups- 57 mins, 32:22 seconds

Longest streak of talking among groups= 2

Lots of Collaboration due to the workshop.

Apple Setting the Trend


Towards the end of Tuesday’s class there was an argument about the utility of some of the Apple Watch’s features. The main topic of discussion was the feature allowing users to send their heartbeat to friends. Rather than making an argument addressing the potential pros and cons for this feature, I’d rather look at the progression of electronic trends and Apple’s role in setting them.

While people now may look skeptically at the apple watch and see it as an interesting and perhaps intriguing piece of technology, maybe in five years people will see the watch as an essential part of their wardrobe. Trends are extremely viral and unpredictable and if the watch is even half as successful as Apple’s recent innovations (ipod, ipad, iphone) it will become essential for a large quantity of people.

The same viral and unpredictable nature of trends can be applied to some of the more obscure features of the watch, like the heartbeat. The concept of sending selfies back and forth may have seemed foreign a decade ago but now is engrained in our culture. Perhaps in a couple of years people will be sending their heartbeats back and forth. Maybe that technology will evolve into a whole new trend. While these trends cannot be predicted, Apple will probably be leading the charge with their extremely loyal following and their ahead of the curve products. In conclusion I would say don’t sleep on the Apple watch. I would not be surprised if in a few years the Apple watch will be as commonplace as Apple’s other products.