Revisiting Digital Mourning

In class on Tuesday, we discussed different forms of online mourning, and concluded that digital spaces enable affected individuals to connect with the deceased-and with other living people-on an equal plane. Whereas funerals occur once, take place in a set location, and are often closed ceremonies, digital memorial sites (whether Facebook pages,, or online archives) can be constantly revisited and revised. One of these places we explored, “Our Marathon,” resonated with me especially because I am from Boston and have experienced spectating at the Marathon both before and after the events of 2013.

Should mourning be contained by boundaries?Should mourning be contained by boundaries?

I have my “JFK Moment” from when I heard about the bombing; I was in the Chic-Fil-A in Huntersville and had just ordered a sandwich when a New York Times notification appeared on my phone. I first checked with my friends at home who would have likely been at the race to make sure they were okay. Thankfully, they all were. I did not know any of the four people who died from the bombing, nor did I directly know anybody who was injured, outside of mutual friends. Yet I felt some sort of attachment to the story and still do. Today, the site is relatively unmarked. The two explosion locations have been cleaned, and makeshift memorials have been placed in city archives. “Our Marathon” thus becomes a place where mourning lives on. I was affected by the event, but never would have been invited to the funerals of any of the victims. Thus, private grieving would be closed to me. Nevertheless,  I still feel connected to what happened; to think that someone from New Mexico or France wouldn’t be as connected as be simply because of their area code is shortsighted. Such platforms allow the plane of grief to be leveled between all people. Tragedies bring people together; how can media help unite differences in times of happiness as well?


The Desire to Mourn: A response to our mourning discussion

During our class discussion about online versus offline mourning, my table came across a post on the 9/11 memorial website in which someone claimed that their three year old son was very much impacted by the fall of the World Trade towers, since just a day before he had built two towers out of food cans. This strange posting on the website led to discussion at our table about the lengths people seem to go to in order to connect themselves to a tragic event during times of mourning, and how online mourning can facilitate this desire.

Several months ago, one of my high school classmates was killed by another of my high school classmates. The event certainly shocked many people of the community, including not only those who were close friends with the victim, but also acquaintances who may have only met him a few times. His Facebook page became a type of memorial, where people posted about the great guy he was and memories they shared with him. It was strange to see people who barely knew the victim making long, mournful posts on his Wall. I even remember pondering whether I too should post something. Though I had not spoken to him for several years, I felt that I wanted to be a part of mourning. Ultimately, Facebook provided a platform for me to publicly be apart of this shocking community event even though I barely had any kind of connection to it.

This summer, I saw a documentary on Netflix called The Woman Who Wasn’t There about a woman who desperately wanted to be a part of not only the 9/11 mourning, but also the event itself. Though most of the story took place in an offline environment, I feel that this documentary captures the feelings I have attempted to express in this post. I found it a fascinating tale, and would highly recommend it. Below, I have embedded the movie trailer.

Visualization Reimagined


Database visualization seems to be particularly relevant to discussion about life and death represented through digital media. Nick Gagnon made an interesting observation through his analysis of Jonathan Harris’ Whale Hunt. Gagnon notes that he was initially inclined to interpret the way the data were visualized to represent excitement in the photo series or death of the whale, only to realize after investigation that “spikes” in the visualization connoted frequency of photos over time.

Gagnon’s observations highlight how subjective observation and experience of database representation can be. In class, we touched on the fact that that Adobe’s Flash standard is used to codify the digital information of Harris’ work. Because users are asked to install Flash software to properly compile and represent the work they are able to see it largely as Harris intended, but viewed critically one could call Harris only one “reader” of his own work in the post-structuralist tradition. He can say that his narrative can only be represented in one way, but one can argue that if his work is understood of as a database, it can be represented in many ways.

Screen Shot 2015-03-31 at 9.00.43 PM


Flash rendering: narrative? database?

Screen Shot 2015-03-31 at 9.00.57 PMSource code: narrative? database?

Is the source code for a program a valid representation for the data therein? If a programmer can visualize the code in her mind’s eye, does that constitute a narrative? These questions remind us that representation is a multifaceted process with many layers; equally important to the form of a work is its function.

Weekly Response


In this post, I would like to respond briefly to Richard Hendrix’s Disintermediated Existence. The presence of internet creates public and private spaces for people to share experience, thoughts and emotions. It is truly the process of accumulating memories which are stored in digital form. People are free to participate the discussion about life and death, but meanwhile, they are creating their own memories, perspectives or personalities. In this process of disintermediation and de-aggregation of information, people are making their own “democratized creation” in various ways.

Another great example is Jonathan Harris’s The Whale Hunt. The entire week’s record constructed with photos can be a database itself. But through the narrator’s point of view and the clear time-line, it also tells a story and represents a collection of memories of many others. Does it objectively reflect what has happened during that week? Or at least, the point-of-view of the narrator? Since the representation of things happen in real life can be deemed as certain forms of productions, how do we define or differentiate what is genuine and true from what is embellished or even fabricated? It is certainly very interesting that someone brought this up in class today.

After all, how people interpret the information provided just like how they judge things around with their own values. This resonates with Ryan’s perspective of the social norm on the internet. The question that Ryan asks at the end is thought-provoking,

“Are the things you read on the internet really expressing both sides to the story or is the content inhibited by social norms?”

I also want to raise a question: do the things people put down to represent their perspectives online really represent what they are?


Disintermediated Existence


Distraction becomes all too easy as we are awash in the cornucopia of advancements spurred by the digital revolution. With eyeballs fixed to headlines about the next iPhone or pictures of crushes on FaceBook, existential questions can tacitly seep into the shadows. It is often said that nothing can hide in the watchful eye of the NSA in today’s database-driven world, but a few new things are born when the entropic force of time is abated even slightly. Death is a fundamental element of human existence, but it would seem that even the dissolution of existence into the sands of time can be partially abated.

While a best friend may pass away in the real world, their FaceBook profile, emails, game avatars, and other digital paraphernalia continue to live on in cyberspace. The mourning process is also evolved. Joyce Walker notes that,

Not only did the Web allow for the creation of both public and private spaces for the activities of mourning, it also allowed these spaces to exist in direct cohabitation with sites developed to meet other rhetorical goals (i.e., information sharing, news, and political discussions).

In other words, with a transformative medium of information exchange and culture creation comes a new paradigm for existence, mourning, and death. Cultural cross-politinaton takes place between political and personal spheres. These new modes of sociocultural interface were brought to the forefront by the events of September 11, 2001. For the first time, news and images of these events were disseminated globally over a medium that not only allowed for democratized consumption but also democratized creation. Lee Manovich considers this new form of interaction as “telepresence” describing it as

one example of representational technologies used to enable action, that is, to allow the viewer to manipulate reality through representations.

The key element of this new reality lies in its negotiability. People don’t have to experience these events and mourn them through one-way channels like television and radio (transformative in their own right), but they are able to actively participate in defining the life, death, and memory. Because this cultural exchange itself takes place over digital mediums in databases, these processes can themselves be studied and evolve understanding over time.


Studio D’s Screens: Where We Look

DIG 210 is my third class in Studio D. As we all know, the room functions pretty differently from other classrooms on campus: moveable desks, a laptop cart, whiteboards around the perimeter, and four monitors make the space pretty flexible. Whereas most rooms contain rows of chairs that face in one direction, Studio D’s design makes students constantly change who (and what) they are looking at. For my observations this week, I focused on the room’s monitors: I know that I don’t have my “go-to” screen in the room, and was curious if other students switched the screens they looked at as well.

The diagram below shows the four monitors in the classroom. On Tuesday, there were three moments in which students were asked to look at a screen: the first and second related to blog posts, and the third related to our discussion on annotating the Apple Watch website. On Thursday, Moment 1 represents a review of the course syllabus, Moment 2 represents pre-Gephi discussion, and Moment 3 occurred after the Gephi demonstration concluded. The following results describe the screens students focused on for each of these moments:

Moment 1: Screen 1: 7, Screen 2: 4, Screen 3: 3, Screen 4: 3, Personal Laptops: 10

Moment 2: Screen 1: 6, Screen 2: 6, Screen 3: 3, Screen 4: 3, Personal Laptops: 9

Moment 3: Screen 1: 5, Screen 2: 2, Screen 3: 2, Screen 4: 0, Personal Laptops: 18

On Thursday, The following results describe the screens students focused on for each of these moments:

Moment 1: Screen 1: 1, Screen 2: 1, Screen 3: 1, Screen 4: 3, Personal Laptops: 20

Moment 2: Screen 1: 2, Screen 2: 0, Screen 3: 1, Screen 4: 10, Personal Laptops: 13

Moment 3: Screen 1: 2, Screen 2: 2, Screen 3: 2, Screen 4: 7, Personal Laptops: 2

Thus, it becomes clear that students in Studio D do not focus on a single screen; instead, they alternate the direction toward which they pay attention. I’m not sure whether this is a good or bad thing- or neither. It certainly does contrast sharply with typical classroom settings, at least. Tuesday saw more students looking at the screens across the classroom’s walls than on their own devices.

Class Diagram
Class Diagram


Incomplete data of students speaking up in class



Date No. of times that students spoke up No. of students that spoke up The most times a student spoke up
3-Feb 26 15 4
5-Feb 10 8 3
10-Feb 17 12 4
12-Feb 18 11 3
17-Feb 23 13 5
19-Feb 15 9 3
17-Mar 40 15 7

Since last time being an observer, I decided to continue with a set of data in the following classes. The set includes the number of times that students spoke up in total, the number of students who spoke up and the most times that a student spoke up in each class. I tried to separate asking questions, or very brief conversational responses from a legit speak up. Thus, in my definition of speaking up, it should be a student that explains concepts, demonstrates thinking or answers questions. Any conversation that involves very short sentences or clarifications of certain words is not counted.

However, the data is heavily influenced by many possible factors. For instance, the attendance of each class could affect all three types of data. Also, the content of the class could affect the data, such as the “fish bowl” on Feb. 10th. Since “fish bowl” is not normal speaking up in class, the discussions are not counted into the data. Also, on Mar. 17th, the topic involves Apple Watch in which many people have strong interest. The total times of students spoke up is considerably high.

Nevertheless, the most times of a student spoke up in class doesn’t vary much. An assumption is that people tend to not to speak when they think they have already spoken up enough many times. From the data, the limit seems to be around 4 or 5 for people that usually speak up.

The data is incomplete since the collecting process was not consistent. Also, the counting process is performed by only me. I could possibly miss one or two times while taking notes or listening to anything that had my attention.

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.

Class Participation, Bracket Style

Since we’re in the middle of March Madness, I decided to track class participation in a bracket-style tournament format. A student advanced each time he or she directly addressed Dr. Sample in class discussion, or if Dr. Sample called on them to answer a question. One could only advance if there was an opponent available to defeat (therefore, someone who answered five straight questions would only win one matchup, not five). Although I could have played the role of the selection committee and “seeded” the field, I chose to use the list of names from the blogging groups page in the order they are listed.

The results from Tuesday’s class are below:

observations 3.20

Unfortunately, we ran out of time on Tuesday to determine a single winner. Also, the Gephi workshop on Thursday prevented the bracket format for serving as a good measure of participation (since we spent more time discussing in tables rather than as a whole class).

Although the bracket exercise was certainly amusing, it doesn’t appear to be the best way to determine the “best” participants; a lot of people who were bounced in the first round ended up speaking a lot later in the class, often more than the people who originally eliminated them. Perhaps the same critique could be applied to the NCAA basketball tournament as well.

Clothing choice predictive of class participation?

This week I collected data to see what clothes people who participated in class chose to wear. Continued collection of data like this could investigate to see if there is a correlation between the clothes people wear and whether or not they participate frequently in class. However, I only collected the data for Tuesday due to the workshop nature of Thursday’s class, so it will only provide a snapshot of class participation.

Tuesday, March 17:

5 people wearing pants –> 6 participations
21 people wearing shorts –> 13 participations

9 people wearing long-sleeves –> 6 participations
15 people wearing short-sleeves –> 7 participations
2 people wearing no-sleeves –> 5 participations