Sara’s media diary

I used Rescue Watch to track my media consumption but was not completely satisfied with the detail of reporting I received at the end of the week. I would have liked more in-depth information about the sites I was visiting (rather than the top three per category), as well as how the program chooses what to classify as “news and opinion” vs. “references and learning” etc. Another problem with this program is I have a very dangerous tab habit in which I average about 40 tabs open in a browser at at time and they may stay open for weeks…so I think the time analysis per page was somewhat skewed,  Nonetheless, the snapshot view provided by the platform as well as some additional reporting and recording on my part provided me with a few takeaways:

  • Like most people, scheduling and communication, primarily on email and calendars, was the single greatest individual category of media consumption. According to Rescue Watch, it was 36% of my time and a total of 8 and a half hours over the course of the week. That actually seems pretty low to me and I wondered about the nature of the tracking. This did not include emailing and messaging on my phone. .
  • The rest of my top 5 was pretty expected – numerous course readings,  the New York Times and Amazon (streaming TV shows). I also spent 4 hours actually going to the movies (the perks and joys of a long weekend).
  • Digging a bit deeper into my browser history, while a significant number of the sites I visited were news and opinion sites, I spent far shorter periods of time on each page, meaning I am either a faster or more superficial reader than I thought.
  • My news consumption started daily with a broader reading across international, local, national news and arts sections (though perhaps limited in ideological perspective) and then became increasingly more narrow in scope and theme as the day progressed. This was because most of my clicks either came from social media where like-minded friends were posting on the issues that I care about or through the various thematic email newsletters I subscribe to (Latin American politics and human rights, media industry, freedom of expression and press freedom etc.). Besides the Times, my reading was very piecemeal with never more than one or two articles a day from the same news source. I realized through this exercise that while my daily news consumption may include a variety of sources, aside from the day’s top stories, the subject matter was generally more or less always the same.
  • The big surprise and rude awakening was the fact that shopping came in as the third ranked category on my rescue watch list. I am not a big online shopper so did a little more digging and realized the program was reading my Amazon time as shopping, rather than streaming content. Nonetheless, I did attempt to buy a couch online this week and this program laid bare all the wasted hours on this failed enterprise.
  • Main conclusions: unsurprisingly, I spend a lot of time writing and responding to emails, reading the news and going to the movies. My indecision means I should not be allowed to online shop for furniture.
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Anne C’s Media Diary

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I set up Rescue Time after our first MAS.700 class (February 8) and tracked my time through February 21. I entered offline time, trying to be especially diligent when the time was dedicated to media consumption. For example, during this time period I spent a considerable amount of time reading actual print media for another course I am taking.

I found Rescue Time to be fairly accurate, though I had to customize and clean up the data. I removed times that were idle (i.e., new browser tab, login screen).

A day-by-day comparison of top activities reveals Facebook is the top single time consuming activity.

Comparison of Media by Day

Comparison of Media by Day

When I customized the categories in Rescue Time to reflect their productivity value, the data revealed a shocking amount of time is spent on social media (e.g., Facebook, Twitter). Perhaps it shouldn’t be that surprising, but seeing it displayed in a bar graph, provided visual confirmation of my suspicion.

Media by Productivity Categories

Media by Productivity Categories

The visual display of my “productive activities” showed a fairly high amount of engagement spread across a variety of tasks.

Another useful visual is the output of productive versus non-productive engagement by time of day. My productive time, which includes reading, research, and writing occurs between 2:00pm and 10:00pm. There is a large spike in social media use around midnight or 1:00am, during which time no actual work occurs. Additionally, I often have some type of video streaming simultaneously at this time. This content ranges from news reports to comedy clips to TV shows.

Media Consumption by Time of Day

Media Consumption by Time of Day

This was a useful graph as it helps me understand how my schedule breaks down. I would have hypothesized that my most productive time actually began around 10:00am, but it turns out that time is spent on email and scheduling—time that is spent using gmail, google calendar, and other similar tools.

I come away from this experiment with two commitments. First, I would like to cut my communication time in the morning from two hours to one hour. My second goal will be to reduce my overall social media time, especially during the window of time before I go to sleep.

I will repeat to myself, “there’s no such thing as multitasking” and try to avoid losing efficiency by working on unrelated topics at the same time.

Drew’s media diary

After tracking my computer usage for 6 days, I was interested in three questions:

  1. How often do I use my computer for consuming, and how often do I use it for producing?
  2. Which are the websites I consume from the most?
  3. By studying the types of media I consume, what can I learn about myself?

Tracking all my media usage was not as difficult as it may have been for others in the class. I don’t use a smartphone, so I have no mobile consumption (beyond phone calls!) I occasionally read print sources, such as The Tech, but that contributed to fewer than 30 minutes this past week. Almost all of my media consumption is done through my computer, which I’ve been tracking with an application called Timing.

To answer the first question, I reviewed all the time I spent on my laptop and divided it into two broad buckets: productivity and media usage. This was more of an art than a science. I thought of productivity as any application or website in which I was actively producing something (e.g. writing something in LaTeX, composing emails, reading a pset on the computer while solving it on paper, buying stocks, etc.)

These tasks served as a nice benchmark for the thing I was really interested in: my media usage. I defined this category as anything that wasn’t “productive” as defined above, i.e. consisted almost entirely of consumption. This included reading news or blogs, browsing Facebook, or even reading other posts on this website!

Granted, these categories were separated by a fuzzy boundary at best. Some things like email were hard to classify: when was I consuming emails and newsletters vs. when was I preparing an email? Furthermore, Timing had trouble knowing when I was actively viewing something on my computer, so all the data should be treated as having huge error bars. (Times are probably underestimated.)

I believe the results still yield interesting results, however:

My media consumption is (thankfully) consistently lower than my productive uses of the computer. It is still considerably large, however. What surprised me was that I wasn’t spending a lot of time on any single website, but rather that I was spending a little time on many websites, which added up to significant periods of time in “consumption mode.” (See the chart below for more context.) Consumption in the age of the Internet is incredibly distributed.

My overall usage of the computer was lower on the weekend as expected (see Feb. 18, a Saturday). However, the weekend is also when the highest percentage of my computer time is spent on media consumption.

The chart below sheds light on my second question:

Google Hangouts, which I included in media consumption (although that could be debated), took up 149 minutes because of several videochats I had this past week. (One of these was a conversation with other Americans across the country discussing the recent political events.)

As a subscriber on the NYTimes, I’m happy to see it make it into my top 3, and the time I spent on it is about what I’d expect.

To answer the third and final question, however, requires a more aggregated analysis:

This chart yields the most value for me.

Social websites like Facebook and Twitter are having a large impact on how I see the world, even if I don’t go there for traditional news. That’s because they make up over half the time I spend consuming media on the computer. Just by the nature of scrolling through their newsfeeds and adhering to their algorithms, I am being shaped by them.

I don’t read the mainstream media (like NYTimes, Washington Post, and WSJ) as much as I would expect. When I think about where my opinions form and where I find the facts that I reference in conversation, they usually stem from these mainstream sources. However, given that only a fifth of my media consumption comes from there, I must be weighting these sources substantially higher in my head because of the perceived credibility that comes with them.

I was happy to see that new forms of journalism (like BuzzFeed and MuckRock) are the next largest category. These are sources that can provide alternative perspectives and in new forms. I intentionally try to seek them out, and so it was reassuring to see that I’ve been somewhat successful in keeping up with it.

~

To end on a fun note, here are some fascinating tidbits that I picked out from my week’s worth of data:

  • The longest time I spent on a Wikipedia page at one time was 7 minutes. Article: “Gas constant
  • The news websites that didn’t make it into the charts above (because I visited them for under 3 minutes) included CBS Sports, NYPost, The Independent, The Verge, Huffington Post, Fox News, and The Crimson.
  • I like to visit BuzzFeed occasionally because they have some great original reporting. However, I still don’t spend as much time reading them as I would like! See below:
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Anne’s Media Diary

From Sunday 2/12/2017 to Saturday 2/18/2017, I tracked my media consumption with RescueTime on my laptop, RescueTime on my phone, and logging time by hand.

This is how RescueTime and my discrete hand-logged records claim I spent my time:

However, my own logs showed the real picture.  With my laptop, a second monitor at home, my phone, and countless apps, I’m constantly multitasking, or at the very least, switching between activities.  

I send my friends excerpts from news articles as I read, providing (unasked for) running commentary.  I run Netflix in the background as I plan out my day in Google Calendar on my second monitor.  I read a case for class, and WhatsApp notifications pop up on my phone, so of course I check them.  

While listening to music on my phone and walking to class, I scroll through Facebook, see an interesting article posted by someone I vaguely remember from summer camp a decade ago, Gchat the link to my friend from college, and start chatting about it, continuing throughout the day.

I originally thought this would be a lesson about distractions and lack of depth in media consumption, but it’s instead about the discussions.  Over the last year, I was oddly proud of myself for actively trying to see other perspectives by actively clicking on Facebook links posted by people with different ideologies.  But that isn’t sufficient — there’s a difference between simply consuming information and being immersed in discussion about that information.

Tyler’s media diary: Using data to break bad habits

I had a suspicion going into this assignment that I’ve developed a few really bad media consumption habits:

  • I spend too much time on Twitter, which is skewing my perception of news coverage.
  • I “graze” way too much, opting for reading headlines instead of reading stories. This means I’m much less informed than I think.
  • My desire to be constantly “in the know” means I almost compulsively check social media first thing in the morning, throughout the day and last thing at night, so it’s more difficult to balance my media diet.

After tracking my media consumption from Feb. 15 through Feb. 20, I can confirm all of these three bad habits are true. The problems may actually be underrepresented, given that this period was a fairly atypical week (as I’ll explain).

Because I wanted to track media consumption across multiple platforms, I opted not to use RescueTime and noted everything manually in a Google Spreadsheet as the week went on. I cross-checked entries with my Google calendar, browsing history and Twitter history to make sure I wasn’t missing anything. I didn’t count reading email, unless there was some specific content there that fit the definition of “media” (a newsletter, for example).

The first big finding is pretty glaring: Social media accounts for nearly a third of the time I spend consuming media. Break that down further, and you can see that within the social media category, Twitter takes a lot of the air out of the room.

Twitter is followed by Reddit, which I mostly consume at night before I go to sleep (I also need to cut down on how long I play video games, an issue I blame solely on Stardew Valley).

I’ve made a concerted effort over the last few weeks to spend less time on Facebook, which is why it appears so small in the chart.

One thing to note about the time period recorded: Over the long weekend, I took an out-of-town trip with friends to a spot without great Internet service. I suspect that if I were to repeat the media diary for the next few weeks, there’d be even more Twitter usage, although this may be offset by more media consumption in general.

If I had to guess before taking a closer look at the numbers, I would have said I spend far more time consuming media by phone than by laptop. That’s clearly untrue.

Also of note: I despise online video. Although I didn’t graph this particular breakout, almost all the video I consume is through the TV (in this case a Roku stick), and not through mobile or laptop. And although I do often listen to podcasts, NPR or other broadcast media, I didn’t really do that over this time period.

So despite some data collection problems, it’s pretty clear I’ve got some media consumption issues I want to address:

  • Spend less time on social media — specifically Twitter.
  • Seek out platforms that use more than just immediacy as the driver for news judgement: Instead of the “happening now” on Twitter, find what news editors think is important on the home pages of local and national news organizations.
  • Change the nighttime routine: Use the evening to read physical media or dive deeper into stories flagged online earlier in the day.

Two tools I think will help are Nuzzel, which alerts you to stories being shared often in your timeline, and Pocket, which allows you to save stories and other content you see through either your mobile device or laptop to read later. I’ve already signed up for these services, but I don’t use them often enough to help me consume more content, instead of just reading headlines.

Mika’s Media Diary

I moved from my home country to Boston a couple of months ago. My everyday routine has completely changed including the ways I gather information through the media.

  • In Japan, I used to read a newspaper, magazines and books, watch TV (7 terrestrial and 2 satellite channels), and checked social media feeds in Japanese.
  • In Boston, I’ve subscribed to digital editions of newspapers, cable TV channel RCN (287 channels) + TiVO + TV Japan , Amazon Prime Video, and radio podcasts. The social media feeds I check are in English.

This week’s assignment was interesting because I wanted to know a few things about myself. Has my TV watching habit changed in a new country? Am I getting good information? And have I succeeded in escaping the filter bubble, which was an idea that I was determined to work on after the election?

I used RescueTime and time-logging by hand for 7 days between 2/8 to 2/14 and created the below visual based on the data from 2/9, which was the day I spent the longest hours consuming the media. Electronic devices that I checked were 2 smartphones, 1 tablet, 2 computers, a TV set and TiVo. In order to focus on the type of media, I excluded the time for business, research and communication.

This assignment has given me a chance to review my everyday routine and opened my eyes to an important fact. I no longer care if my current habit is different from my past or if it is balanced or not. It has been a cold winter. I often chose to stay at home. But now it’s time for me to stop being a consumer and start being a producer.

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Arthur’s Media Diary

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Source:

This analysis is based upon 2 tracking apps – Moment on my smartphone, and RescueTime on my computer. I did not consume any content through any other devices (no books, newspapers, or TV)

Time Period:

  • RescueTime: Feb 8, 2017 – Feb 18, 2017
  • Moment: Feb 14, 2017 – Feb 18, 2017

Mobile Consumption Analysis

Using the Moment app, I tracked how much time I spent by application for 5 days.

This was not super insightful, so I bucketed the apps into these categories:

Using these categories, the analysis became more clear:

Communication and Content Consumption seemed like the most prevalent categories, but Content Consumption seemed more relevant to the nature of this assignment so I looked more closely into that category.

As this chart shows, Facebook (in gray) and YouTube (in orange) make up the majority of my sources ON MOBILE. This makes total sense:

  1. When I’m on the go, I browse through FB, and any articles that I find and read are opened within the app
  2. When I am walking, I don’t like to read much, but still like to stay up to date on news, so I typically find YouTube videos from various news networks and watch those. This explains the high YouTube minutes on 2/14, 2/17, and 2/18. On 2/15 and 2/16, during my walks to/from the T, I was on the phone, and so couldn’t consume content those days (This can be seen in the chart above, where the “Communication” category has relatively more minutes those days as compared to others)

Desktop Consumption Analysis

To analyze my media usage patterns on desktop, I had to rely on RescueTime’s free online dashboard tool.

Looking at the overall productivity summary didn’t really tell me much:

Looking across the dates, a couple things stick out:

  1. Something good for my sanity is that on weekends (2/11 and 2/12), I spend less time than most weekdays. (It also makes sense that on Tuesday (2/14), I also had relatively low time, since that’s my most class-intensive day)
  2. The split between productive time (in blue) vs neutral (in gray) vs distracting time (in red) doesn’t seem to showcase any interest trends. However, I think that’s because it’s very unclear what falls into each of those categories

Let’s try to explore that further:

As I start looking into the categories, some interesting insights start to appear:

  1. YouTube is CLEARLY my entertainment of choice….. and while I’d like to think most of that time consists of watching various news segments, realistically, I’m sure a solid proportion of that is more in the cat-video-category of content….
  2. Email and messaging (WhatsApp) take up a massive portion of time, and while that may seem surprising to most, I’m not surprised. The reality of most work today is that it is collaborative by nature. This means these tools are critical to that
  3. I’m glad facebook is not in any of these top 3 categories, yet I’d love for this to show me how much of my FaceBook time is spent reading articles

Diving a bit deeper into the categories….

I’m beginning to think that I really don’t read or consume as much content as I thought I did! All of the displayed categories are not content consumption sites (Facebook articles would link out to different tabs so would be counted separately). 

Looking at the day by day breakdown, the light gray category (Everything else) is one that I really wish I could learn more about. I’d like to think that this is the collective aggregation of my browsing and read various news sources.

One additional way I tried to check if I could dig deeper was by looking at time breakdowns by Category.

“Reference” is 3rd highest category there, which I thought could indicate consumption, but double-clicking on that, I saw that it was pretty much all OneNote and Adobe Reader (which are the tools I used most for homework and interview prep).

“Uncategorized” was in the middle of the pack, but double-clicking on that just showed me a bunch of sites associated with classes and the companies that I was interviewing for last week.

Finally, I decided to look at how the time split out by day

Looking at these categories, I would say “Communication & Scheduling” (in light blue), “Reference & Learning” (in light green), and “Design & Composition” (in dark green) all reflect time spent being productive for something career or education related, and they take up about half of the time each day. These represent a tight mix of both consumption and creation.

Overall, I’m pretty happy with this analysis highlighting that I tend to spend time pretty effectively and manage to stay on task. However, as noted before, I would really love to further understand the “other” categories and specifically how my YouTube use breaks down between more useful, news-oriented content vs the youtube black hole of cat videos 🙂

Snoozing differently

By Anne, Jeneé, Michelle and Tyler

Our group discussed a common problem with wake-up apps: How often we hit the snooze button. So we came up with a feature that allows the user to set up two separate playlists — songs you love and songs you hate.

When the alarm clock rings, you can select the “hype” playlist or the “hate” playlist for the next time the alarm sounds to get you out of bed. We also discussed ways to integrate the alarm app with services like Spotify and Pandora and use them to further randomize the hate/hype based on the preferences you’ve already stored.

 

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