Kitty, Vivian, and Bianca uncover the peanut gallery

Check out the demo of our commenting system here: http://um-viz.media.mit.edu/finalFON/index.html
As the news industry has evolved, individuals both inside and outside of established media corporations have made efforts to improve the processes of news consumption and production.  Emerging technology allows users to interact with and produce news and broadens both the reach of the news and the range of individuals who can help create and spread it.  While the process of writing and disseminating news has become more participatory, very little meaningful work has been completed and implemented towards improving systems that allow readers to react to and interact with news and other media content.
Often overlooked and undervalued, comments can provide a rich opportunity for discussion: they provide a portal to understanding how news is received, points of contention, and further resources to delve deeper into the topic at hand.  Comments allow the reader to interact directly with the content and the news producers rather than passively consuming material.
For our final project, we explored methods for creating more engaging comment experiences through visual cues, responsive environments, and audio snapshots. One of the great functions of news is to get people talking and debating,  informing them of possible perspectives and involved parties. A comment section should then be a large support or platform for such discussion but it has yet to be perfected in terms of layout,  design, expressive control,  and even analytics. Here,  we are exploring possibilities in the design of comments to reflect user emotion and tone through a mix of sentiment analysis, typographical behavior detection, and a new type of censorship (yay, censorship!!)
In existing systems, all speakers are given the same visual weight, and all words are displayed in the same manner.  We started by asking how reviews and responses could be reinterpreted by more clearly signifying speakers who were representing a business or organization (in the context of Yelp), but instead we chose to provide more implicit features for every commenter.
As it stands, all words and tones are given the same typeface and size.  It can be difficult to parse through and understand sarcasm, irony, anger, and genuine enthusiasm.
Our goal was to answer whether or not changing the design of comments could change the way we interact and read them for the better. In exploring the power of comments and attempting to amplify their richness, we considered the role of lurkers (those who passively read, and potentially vote on comments, while not actively commenting themselves), active commenters, and the authors and publishers themselves.  Part of efforts to amplify comments result in and include creating an environment that is more readily scannable.  This was achieved via two means:
A) Visual Effects:
– repeated letters are translated into larger letters and letters of increasing size
– flowery letters and butterflies to mitigate curse words
– positive words are colored red, negative words are colored blue
– ellipses turn the previous word into fading one
– exclamation points turn preceding words “Large yelling” words
– increasingly positive words become darker red
B) audio soundscape
– drawing from the quantity and sentiment of the comments, the play button produces tones and sounds that represent the fervor and tone of the comment field
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Vivian and Bianca (attempt) to explain mental health at MIT

…and end up confused.

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Check out our article here: https://medium.com/@biancadatta/mental-health-at-mit-54b7d0b68f75

We were expanding upon these Boston Globe articles:

  • http://www.bostonglobe.com/metro/2015/03/16/suicide-rate-mit-higher-than-national-average/1aGWr7lRjiEyhoD1WIT78I/story.html
  • http://www.bostonglobe.com/metro/2015/03/01/third-mit-student-commits-suicide-this-school-year/TxljHhCHGQIROChsA5JoqI/story.html
  • http://www.bostonglobe.com/metro/2015/03/06/mit-freshman-dies-eighth-death-school-community-last-year/P3DueFWGsMXXRdnskOTuIM/story.html
  • http://www.bostonglobe.com/metro/2015/03/16/mit-students-open-about-stress/dS61oA5tiKqjvVsJ5VZRAL/story.html

 

 

 

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This is not a hologram

This week, Carol and I wanted to explore the idea of conveying complex scientific information while debunking some common misconceptions on display technology.

In the upcoming day(s), we’ll work on creating a more immersive presentation that employs parallax, but for now, check out our thoughts on Medium: https://medium.com/@biancadatta/this-is-not-a-hologram-324310087bcc

2010.11.holograph.infographic

 

 

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Bianca and Vivian (Heart) Science

This weekend, Vivian and I decided to the explore the I (heart) Science event at the Harvard Museum of Natural History (http://hmnh.harvard.edu/event/i-%E2%99%A5-science).  The event gave us a chance to interact with some (adorable) children and their families, as well as some awesome experts, and some creepy critters.

To present our findings, we created an interactive version of the museum map.

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Take a walk through the exhibit (starting at the Earth & Planetary Science room and moving to the left) to meet some of the characters we met.  Click on the red squares to explore.  (Check out our project here: http://um-viz.media.mit.edu/4hoursF/index.html)

(PS: Check out the Evolution room for some truly brilliant insights from the exhibit visitors

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Insights and commentary: Though we chose the event as we thought it would be a fun environment that would provide some interesting opportunities for interactions (and the opportunity to stare at pretty rocks), we ended up gaining a really interesting perspective on how an effective implementation of STEM education outreach actually works! Here are some of the components that we isolated.

Roles: (see character profiles in our map for more details)

  • Hobbyists
  • Experts
  • Non-expert volunteers
  • Visitors
  • Parents
  • Kids
  • Community Members
  • Educators

Features:

  • Interactivity
  • Resources/accessibility
  • Live demos
  • Bite-size pieces of info (with the potential for in-depth exploration)
  • Portrayals of reality
  • Juxtaposition between high and low-tech
  • Wide-age spread

Character profiles included in our map: (Toby Flowers- Rock Ninja, Charlie Flowers- Super STEM Dad, Janani and Shivapriya-  Voracious Visitors/ Rad Researchers, George Buckley- Expert)

Results: Fascinating microcosm of the ecosystem of STEM research. 

 

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Bianca’s Media Diary

As many other members of the class did, I began this assignment by using RescueTime to track my computer activities over the course of the last few weeks.  Before I launch into my analysis of the statistics that the app collected for me, I’d like to mention a few caveats:

  1. RescueTime did not account for my phone usage, which (unfortunately) accounts for a huge amount of my “distracted” time.  However, through this activity, I also discovered that this is where I read the majority of my news (the BBC mobile app, for instance) and listened to news broadcasts or informative podcasts.  Thus, my RescueTime statistics lack some of my most positive and negative uses of technology (though positive and negative are potentially extremely subjective here).
  2. The app has no way of tracking time I spent reading or consuming physical media. I go through the majority of my (self-proclaimed) important readings on paper.  I typically have spotify or email up while I engage in physical reading, which (partially) accounts for the massive gmail numbers in the following graphs.
  3. Also, I felt a need to cheat when I knew that RescueTime was monitoring my activities.  This meant that I switched some of my Facebook time to my phone, or tried to more actively visit news sites during this period.  You will note, however, that news does not even show up as one of my categories.  This is both disappointing and unsurprising news.  It confirmed my theory that I only read news in small chunks when in transit, when procrastinating, or when engaging in distractions during meetings.
  4. Some of the categorization seems arbitrary.  For instance, time spent in Evernote goes under “productivity,” even if I was using Evernote to collect fuzzy animal links (I have not yet done this, but now maybe I will).

Alright, caveats aside, here is what RescueTime revealed:

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Perhaps the most important line:

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For the first few days, I tried to manually log some of my news sources:

2/5/15:

  • NYT (15 mins)
  • Facebook
  • Twitter
  • word of mouth

2/6/15

  • 99 percent invisible on commute
  • NYT before recitation

(end of my attention span when it comes to manually logging this information)

I started using Pocket to avoid having three hundred tabs open at any given moment, but quickly discovered that for me, out of sight pretty much meant out of mind, and I rarely came back to those news articles.

The bottom line here: I spend a gross amount of time on gmail and Facebook, and my computer usage is highly unproductive.  None of this is really a surprise to me. It basically revealed a massive underlying level of media distraction in my life.

I have recently been spending a lot of time thinking about attention, focus, productivity, and cognitive space – mainly because my first semester has passed and now I feel a lot more pressure to accomplish significant things (blah blah blah). Part of this has led me to think more about making space to write, reflect, explore, and think.  One of the themes that keeps coming up in my explorations is the idea of crafting physical space to promote (or prevent) certain actions.  With that in mind, I decided to create a type of “map of my desk space” to further unpack my media consumption.

It ended up looking a lot less a desk and more like a 3D bar chart: the diameter represents the frequency of visits to the site/medium, and the height represents the amount of time I spend per visit/use of the medium, so the volume represents approximate total time spent engaging in the medium.  I collected this information through a combination of RescueTime, estimation, and timers.

Here is the key (unfortunately, the colors did not come out super well):

2015-02-17 16.59.49

Laying out my “desk” space forced me to think about how I mentally organize my sources of information.  Ultimately, I realized that I understand and focus on concepts better when I see them on paper, but that for things like news, things that are temporary, I typically need to use digital media.  I attribute this to the rapid turnaround rate – physical versions of these would pile up incredibly rapidly.  Based on this understanding, I separated the categories into “static” (i.e. textbooks, papers, books read for fun, patents, etc.) and “dynamic” (Facebook, Twitter, email, websites/blogs, NYT, BBC, Snapchat News, Messaging).

2015-02-17 16.45.26 (top view)

2015-02-17 16.45.57 (side view)

Gmail (the green blob), was my most frequented site (large diameter), but I used it for relatively short spurts each time (so it is a short bar).  Similarly, the Facebook bar is almost flat as I only ever briefly scan through Facebook, but I do so incredibly frequently.  Conversely, the papers bar is very tall, but has a small diameter- I only sit down to read papers once or twice a day, but when I do, I spend hours on that task.

Looking at this arrangement, I was curious about the sources of my information.  I already know that I receive an alarming amount of my news from messages, word of mouth, or Facebook, but I wanted to further explore my influencers.  I arranged my bars into a venn diagram:

2015-02-17 16.50.10

2015-02-17 16.50.43

I am, by nature, a highly social and socially influenced individual, so it was not entirely shocking to see how much of my media came from friends and outside sources.  It is interesting to note that the things I spent the most time on originated from a combination of my friends and my own investigations. I found this to be both reassuring and logical – that is the most interactive and dynamic space.

One aspect of my media consumption that was not captured with this framework was that I read much faster when read on paper.  I’m not entirely sure how this factors into my scaling plan, but it certainly impacts how much information I process.  It also does not account for the difference between time periods: I happen to be a morning person, so for me, not all hours are equivalent.  I’m much more efficient in the morning, so it takes me less time to get through content and effectively process it than it would at night. Based on my RescueTime stats, I’m trying to consolidate my email time rather than spreading it throughout the day, but it’s sometimes difficult to find the appropriate space to conduct email sifting.

The final aspect of my media consumption that I did not examine was the location of engagement.  For instance, do I read most of my papers at my desk? Do I read the news on the T? I know I mostly listen to podcasts on the way to work, and I mostly read for fun on my couch, but in the future it may be interesting to explore any correlations between location and type of media.

Overall, I learned that I am easily distracted and potentially very unproductive.  There is a lot of room for stream-lining, and it might be worth reconsidering my (lack of) consumption of traditional news sources.

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