Media Diary – Future of News and Participatory Media https://partnews.mit.edu Treating newsgathering as an engineering problem... since 2012! Wed, 17 Feb 2016 04:21:28 +0000 en-US hourly 1 https://wordpress.org/?v=5.2 Track your media: Know thyself https://partnews.mit.edu/2016/02/16/track-your-media-know-thyself/ Wed, 17 Feb 2016 04:18:25 +0000 http://partnews.brownbag.me/?p=7766 Continue reading ]]> Summary

“Track all the media that you put into your head after you leave this classroom”, said Ethan. The exercise was demanding, I did it for five days and the interruptions felt unnatural as I was collecting the data of my Whatsapp’s messages, the news I read or my mom’s FaceTime calls. However, that neurotic gathering of information paid off: at the end it provided a revealing portrait of my media behavior.

Among other things, I discovered that I’m locked in a microscopic part of the Internet, that I’m consuming media one in every four minutes, and that E-mail takes most of my time in front of a screen.


Gathering the data


To collect the data I took screenshots of all the digital media that I consumed via my mobile or my laptop.

150 screenshots in five days

150 screenshots in five days

Then I organized all that information (time, device, language, format, etc.) in a Google Spreadsheet that turned out to be nine columns and 134 rows.


Interviewing the data

I used WTFcsv, a tool included in the DataBasic.io set, to visualize my data and start asking it questions. In some cases I also used the Explore function embedded in Google Spreadsheets.

1. How much time did I spend in front of a screen?
Five days have 7200 minutes, and let’s say that I slept 1800 of them (6 hours per day), so I was awake for 5400 minutes. During the five days of the exercise I spent 1331 minutes consuming digital media: that means that I was 24.6% of my time in front of a screen.

One in every four minutes I’m consuming digital media. That’s just shocking.

2. How diverse is the media that I consume?
Using pivot tables in Excel I found out that I only visited 45 unique websites, that’s an average of 9 different websites per day. There are around 990,950,000 websites in the Internet right now. In proportion, the 45 websites that I visited are like the size of a particle of dust (0.5 µm) in the Big Ben.

dust in big ben

See that speck of dust? It’s what I know of the Internet.

I also discovered that I only used 17 of the 87 apps that I have installed on my mobile… No comments.

3. When in the day do I consume more digital media?
Screen Shot 2016-02-16 at 9.36.44 PM

4. What media format do I consume more?
formats 5. In which activities did I invest more time?
Screen Shot 2016-02-16 at 9.34.15 PM

6. En qué idioma consumo la información?
languages

8. Time invested in each activity

 


Things that I would like to know but that I couldn’t visualize

  • Infrastructure of the Internet. The location of the farthest server that send me information, for example.
  • Gaps in the consumption. Besides my hours of sleep, how much time did I spend without consuming any kind of digital media?
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Wahyu’s Media Diary https://partnews.mit.edu/2015/02/17/wahyus-media-diary/ https://partnews.mit.edu/2015/02/17/wahyus-media-diary/#comments Tue, 17 Feb 2015 21:50:42 +0000 http://partnews.brownbag.me/?p=5418 This is my first time attempt to picture my media consumption pattern in a graphic. Enjoy!

This is my first time attempt to picture my media consumption pattern in a graphic. Enjoy!

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Dalia’s Media Diary https://partnews.mit.edu/2014/02/11/dalias-media-diary/ Wed, 12 Feb 2014 03:48:08 +0000 http://partnews.brownbag.me/?p=3189 Continue reading ]]> For my data collection, I decided to use the application Rescue Time. Rescue Time is ideally used to enhance productivity and manage the amount of time spent on ‘disruptive’ sites. The user can indicate a set of productivity goals with a set of sites that would be considered disruptive and calculate productivity on a daily basis based on media consumption.

 I, on the other hand decided not to set any goals and just record my consumption based on sites visited. I do have to note that I have reservations regarding the pre-defined categories in the application, especially when Twitter and Facebook are considered disruptive sites. I find this problematic, not only because I use both platforms to conduct research, but also because I find that both sites can be valuable sources of information and news. Let alone the fact that other forms of media, such as daily interactions and talks are obviously not recorded and thus not represented in this data set. My other reservation is the fact that I can pause the application and stop recording any media I consume. I have to admit I used it on multiple occasions, which gives a skewed result of how many hours I was online and the media I consumed. Regardless, I found quite interesting results and patterns in the data set which I present below.

When I first thought of doing this assignment, I thought of creating a time lapse video of the sites I consumed using the data I collected from Rescue Time. Unfortunately, I face a number of hurdles, one being that the data collected was difficult to translate into a video. More importantly my search for a tool that would be able to create this time lapse proved futile. I tested out Popcorn Maker, (I recalled someone once explaining how easy it was to use, but also the ability to add comments to the videos) However, when I signed up and started using it I realized that I can only create a video from already published media on the web. Not wanting to duplicate some steps and publish material online to then use for a video, I decided to use iMovie, which I surprisingly had never used (Final Cut Pro was my program of choice.) As I started to compile images and graphs onto the program, only to realize that I couldn’t truly translate what I wanted to do with the data using this program.

I eventually, and for the sake of time decided to stick with an info-graph which you can find HERE. I used the site infogr.am to create this graph, it is one of the many tools that are available on the web that can create info-graphics from raw data.

In addition to the info-graph I created, I decided to look into and present my daily consumption which varied from day to day, especially on the weekends.

Day 1 – Wednesday, not a complete report since I started Rescue Time in the afternoon.

Wednesday

Day 2: Thursday

Thursday

Day 3: Friday

Friday

Day 4: Saturday

Saturday

Day 5: Sunday

Sunday

Day 6: Monday

Monday

Day 7: Tuesday

Tuesday

What became a noticeable media pattern is that I was consuming more social media in the early morning and late night during the day. Whereas during the day I spent most of my time on e-mail, scheduling and ‘learning’ sites.

Over the weekend I noticed that I had more time to catch up on the news. I have to admit as someone who considers themselves a news junkie, the fact that I spent so little time reading the news was shocking. Although, my news reading behavior has changed in recent years and I’ve started to rely more on social media as new source.

Having noted all those observations, I would still place a disclaimer and indicate that the data collected by Rescue Time is not entirely accurate and does not indicate time spent at talks, watching a film or media consumed on my phone.

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