The first words I entered into my “media diary” this week were: “We%, %ay one”.
Why this cryptic message? Because the ‘ d ‘ on my roommate’s 10-year old laptop keyboard wasn’t working. And why was I using such a thing, you may ask? Well, my laptop broke down, which during the first few days of this assignment, led me to take on habits that aren’t representative of my usual media diet. But that turned out to be a really good thing. “Good” in the sense that I experienced and ‘consumed’ media that I’m not usually confronted with. Instead of falling deep into Internet holes, or writing blog entries for hours, my 2-hour daily time limit at the Cambridge public library (which according to library protocol, have to be broken into 30-min segments to give other patrons a chance to use the computer) forced me to rethink my typical diet. When I set out to do my media diet assignment, I intended to count all “input”, be it a lecture, conversations, videos, etc. as ‘media’. But I couldn’t watch online lectures or complete the assignments for the MOOC I’m taking. No time for long stretches of learning, news reading, or random browsing. Instead, I struck up conversations with people on an entirely different end of the MIT/Berkman “tech savviness” spectrum. Issues of access suddenly became very personal.

And you thought your computer was slow? Try waiting 10 minutes and then repeatedly seeing this fella.

First, everything took longer. Not only because the Cambridge library computers are kinda slow,  but because I had to stand in line to use them for 30 minutes at a time. Within my 2-hour time limit, I spent the first 30 minutes scouring course pages for the semester. Then, since no other patrons were waiting, I got to register for another 30 minutes at the sign-up station. At the second computer I was assigned to, I sat next to an older man who gave off a strong odor and was nervously tapping his keyboard while clicking on pictures of (barely clothed) women in his Facebook news feed. It was hard to concentrate because he was repeatedly cursing loudly to himself. And there were so many other interruptions. Another man came up to me to ask whether I could help him check his emails. A third teenager played heavy metal so loud that I was sure his headphones (or ear drums) would, at any moment, pop out. So I opted for tasks that don’t require really hard, sustained thinking.

Yup, stiiilll looadddiinnnggg

My next computer round took me to computer C1. As soon as I sat down, the librarian asked me if I want to move because next to me, one patron was receiving a tutorial from a student. I migrated again, this time to A3. But alas, I was kicked off the Internet. The system thought I had been on the computer longer than I had. Once again, I went to the sign-up desk, where the librarian she told me that because she had observed me helping an elderly lady navigate her browser and find the refresh button, she would extend my time. Those extra 15 minutes allowed me to get one email written, before the pop-up message “Please save your work now. Your session will end in 0:01:00 min” appeared.

At this point, you’re probably thinking that this is a story about frustration with my unintended media diet. Or about the inefficiencies and shortcomings of library computer stations. And it is. But that’s only a small part. Because before leaving, I decided to talk to the librarian (I’ll refer to her under the pseudonym ‘Mary’) at length about her work. And out of all the media I consumed this week (including that which I consumed with a repaired laptop), my conversations with Mary were my favorite bit of media “consumption”. She told me that she’s learned more about people, about her community, and about public spaces than she’s learned at any other job. Patrons come up to her asking her help to find housing on Craigslist (Imagine how hard it would be to get housing in Cambridge without a laptop to quickly respond to emails!), to draft resumes, to make calls. She told me how the library is a space where a lot of homeless and mentally ill people come, because it’s one of the few public indoor spaces available to them. Especially in the winter, when it’s cold outside and they might not have anywhere to go. Then she told me this story about how the other day, she observed an MIT student standing next to a 80 something year old woman trying to make copies of old photographs to send to her family. And when the student helped the woman who didn’t know how to operate the copy machine, both entered a conversation that challenged them to understand a completely different view of and comfort with technology. (At this point, our conversation was interrupted when the same woman whom I had shown where to find the ‘refresh’ button asked Mary whether she could help her make a call to her bank, which she did).

Cambridge Public Library Computer Room

Issues of access and the “digital divide” are concepts many of us are familiar with. I study these issues, but still use my speedy laptop and tech skills to do so. But this week, I was again reminded of the strange contrast of the world’s tech savviest people living next to other residents who can’t find their browser’s refresh button. And what a difference in media consumption that makes. In addition, the experience got me thinking about the severe limitations of MOOCs in so much of the world, where students watch lectures and complete assignments from internet cafes and other public spaces where noise interruptions, slow internet connections or time caps are at least as big of a problem as in the Cambridge public library. How are you supposed to excel in a MOOC when you’re constantly watching your computer time (or at Internet Cafes, might have to pay for it), or interrupted by noises, other patrons, etc. But the experience also got me to appreciate Cambridge for its amazing librarians. After I got my laptop back, I used RescueTime and paper notes to track my regular media habits much more systematically. You can take a look here, if you’re interested in some thoughts about radio consumption. But this week, the first story about my “diet” left me with a longer lasting bite to chew on (please forgive me for the pun).

I decided to track my media intake by logging the number of articles or videos I view throughout the day. Breaking up my intake into four major categories, I kept a tally for each day and translated it to the graph above. I wanted to track the volume of my intake as well as the changing proportions of where my media came from.

The overall shape marks how many articles I finished while each vertical line is a day that had a varying breakdown of where I found my media. For example, February 7th was a busy day with not much reading — it roughly broke down to 3 flipboard articles, 1 paper article, 1.5 email articles and 1.5 facebook articles.

I am not incredibly surprised at this breakdown considering I have been building up a Flipboard addiction. However, I know this graph would’ve looked very different a handful of weeks ago — I am slowly weaning myself off of Reddit, which used to be my major source for all things cats or design.

Wednesday

Thursday

Friday

Saturday

Sunday

Monday

Tuesday

Average and Overview

Most Read Topics

This is my response to the first assignment to keep a diary of my media consumption.

This week, I spent 78.6 hours in conversations. (Yes, I realize this is about 70% of the 112 waking hours in a week. This provides some evidence to my hypothesis that the internet facilitates higher volumes of communication by allowing, for instance, simultaneous chat.) The runner-up category of “entertainment” had 22.5 hours. (Something to take into account is that I spent four days with friends in Puerto Rico. A normal week may be more news-heavy or reference-heavy, but conversations would likely still dominate.)

Thus my media diary assignment turned into a closer analysis of my conversations, especially once I realized that the broad categories of “e-mail” and “social networking” that RescueTime provided me did not tell a satisfying story. I was interested in exploring how many people I interacted with over the course of a week, how much of this interaction was one-on-one, how much of this interaction was virtual, and the diversity of this group. As I did not know of a tool to help track this, I reconstructed this information into a spreadsheet detailing my interactions with each person from hand-written notes and message archives.

I defined conversations as any interaction with someone whom I can consider a personal acquaintance (as opposed to a one-way conversation with a journalist or celebrity) that was memorable to me–this includes in-person conversations, chat, and social media interactions such as someone I have met before following me on Facebook or a friend “liking” one of my posts. (I did not include people whose posts I had “liked.”) I spent about half of my conversations one-on-one and half in groups. My one-on-one conversations were split evenly between virtual and in-person; most of my group conversations occurred in person.

This week, I had nontrivial correspondence with a total of 127 people. (This is an underestimate, as I am already remembering other people.) To give some context, I have 996 Facebook friends, 414 Twitter followers, and 514 LinkedIn connections. Most of my correspondence was through direct virtual communication: e-mail, chat/SMS, or phone/Skype.

Here are some interesting numbers from the week. For 55 (43%) of the people I interacted with this week, it was my first interaction with them this month. Of all of these people 21 were completely new; 19 of them I met in person and most of them are outside of my social network. A little less than half (57, or 44%) of these people are associated with work: either at MIT with me or working in my research area. Half (63, or 49%) of people I corresponded with live in the same city; most (121, or 95%) live in the United States. A majority (92, or 72%) are within five years of my age. About a third (46, or 36%) are female. I interacted with 87 (69%) of these people strictly virtually and 18 (41%) strictly in person.

The number of interactions are about what I expected: roughly 10% of the people in my broader social networks. I had more in-person interaction than I expected and met more new people than I expected, though both were probably a bit higher than normal due to travel. I was pleasantly surprised that I balanced work-related correspondence with other correspondence. The percentage of women is lower than I expected–this may be because I have higher-volume correspondence with individual women. From this week’s data, at least, it seems that while virtual communication is useful for helping establish connections with people I have already met who are within my social network, the more serendipitous connections came from traveling. Over the course of a year, however, it may be that how many people I meet virtually (through AirBnB, Twitter, my other internet presence) outside of my social network may balance out with how many people I meet while traveling.

If I had more time to do this assignment, I would be interested in looking more closely at the following:

• Whose links am I “liking” on Facebook? Whose links am I clicking through across media? Whose links am I sharing across media?
• How diverse is the information I am accessing through these people? How connected are these people to each other?
• It would be interesting to have a notion of how much within my social network/sphere of interests these people are so I can have some concept of how likely someone is to change my opinion.
• It would be interesting to measure different categories of conversation: work, gender, and productivity, to name a few.
• How does my level of serendipitous interaction look over the course of a year and what does it correlate with?
• How can I measure attention with respect to conversations?