|Social life and social media
Builds on project(s)
|Show and Tell Talk Infobox
|2012 QS Global Conference
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Quantified Curiosity is a Show & Tell talk by Amy Robinson that has been imported from the Quantified Self Show & Tell library.The talk was given on 2012/09/15 and is about Social life and social media.
Description[edit | edit source]
A description of this project as introduced by Quantified Self follows:
Amy Robinson is curious. That curiosity led her to think very deeply about her curiosity. What was she curious about? Where do her ideas come from? What inspires her? In this talk, Amy takes us through a really unique method for quantifying her curiosity and what she’s learned so far.
Video and transcript[edit | edit source]
Amy Robinson - QS Conference 2012 - Quantified Curiosity
Hi guys, I am obsessed with thinking about thinking. My name is Amy Robinson and I’m here to share quantified curiosity. I am very curious of how the ideas that I encounter, and the new things that I discover integrate and infuse to form who I am and who I will become. A stranger at a TED conference wants walked up to me and said, ‘Hi, so what inspires you?’ The guy is actually making me think about what does inspire me. It made me think about how the things inspire me change over time. You know, I am not constant; I am very dynamic, but it’s hard to remember how I change and to keep it into perspective. So this five seconds consequently have mattered much more than just five seconds, and I wonder if the same is true for ideas. So I’ve been tracking them, and I’ve email myself interesting things, so when I look at things say an article or I write notes, watch a cool video. Anything that makes me think hmm that’s interesting, I email it to myself. And so for this talk, I have actually compiled six months’ worth of data into a pretty big spreadsheet. Each line is an idea entry, and the data has attributes like a date, a link, like an ingram, which is just the subject in the body of an email. It is tagged with topics and it’s also given an interestness ranking of one being low and five being high. So six months’ worth of data came to 770 unique entries or ideas, and 772 total topics. So once this data is kind of organized into a spreadsheet I was able to analyze it and look at it in a completely new way. So this is a weighted graph of the most important topics. So of all the topics that were used, at least 40 times and weighted either four, which is the green bar for important, the blue bar for most important, they show up on this graph, and you can see based on the importance the most prevalent topic vary. So for example, the green bar most important is journal, which is purely literature and not my personal notes, followed by biology and neuro. Whereas if you look at the blue bar, personal notes come up first and you can often look at these as entries over time, and you can see that these are the most important entries and they tend to occur in clusters. So I wondered you know, do these clusters actually correspond to something? There is a huge cluster in February; 14 items in three days. They actually corresponded to me starting a new side project of photos and notes. It’s a tumblr blog where I just published pictures of my hand written notes. So yes, in that case that cluster was something real and I wondered is this true for the other clusters? Yes, in March there’s another one, 21 items occur in a period of 12 days. It corresponds to something kind of goofy that I do, it’s life bonus emails I send these out now periodically to my friends saying you know share something beautiful, inspiring, and intelligent or you know entertaining that you have discovered in the past week and if they complete this challenge they get a hypothetical life bonus. It rocks the inbox, but again the data actually corresponds to me doing something new. I mean how else can we actually explore this. Were able to form these ideas into Gephi, which is a free network graphing program. Now the way that this graph works is the circles are called nodes and they correspond to the topic that are tagged with ideas. The size of the nodes indicates how many times they were used in tandem with other nodes. The edges, the lines between them are the actual ideas that are co-tagged to different topics. You can run statistics in Gephi to modularize communities, so based on how connected groups of nodes are relative to the overall connectivity of the graph, you can isolate and see distinct communities. So for example, the blue down at the bottom is science and science related tags. The purple is work/ health and you can probably infer that looking at the graph. The red section is TED related tags including TED EX and video. And then the green section was self, and there are some cool things in there like playful, curious, ideas, and Quora that popped up really close to me. But this is messy and it’s very hard to see 10,500 edges, so what you can do is actually isolate individual topics. The yellow dot there is the tag of ideas within all my ideas data. And you can see the little green dots, or the outlier dots off to the side. This exhibits high betweeness centrality. Now in social network graphs that represent people, those node that have a high betweeness centrality are the ones that bridge gaps between very distinct communities. They are interdisciplinary in a way and it made me wonder, could the same be true for ideas, those in-between ideas and how can I decipher this information. So we can look at the graph for beautiful for instance and you see there is a purple dot right in the middle, that’s, that’s tech and when I actually looked at these co-tags, there is a series of beautiful scientific technological videos that I’ve actually compiled on my blog and at amyrobinson dot me if you’re curious to see them. You can also zoom in and look at these red sections, they were closer tagged with beautiful, so TED, TED EX side project I guess it’s a good sign I do for free in my spare time and also insights of beauty and awe and video was the largest in that cluster. When I looked at the graph of video it actually made me wonder how we could take this type of information and make it interactive. So imagine you were panning through this on a computer and rather than just looking at nodes you could actually watch the content, you could watch the videos relative to where they’re tagged and other things. This is a tag for self. Again, yellow is self, and a lot of this was intuitive, TED science. I’m geeky I love TED, but there was one dot that actually very much surprised me, closely related to me, a big green dot, Quora. Quora, the social Q&A network. This is a graph of Quora is highly infused with all the different communities of my ideas. These are beautiful graphs, they are elegant and nice to look at, but you know what do they mean, what can you actually learn from ideas in this type of way? It puts them into context, and by being able to see my ideas and see the way they’re connected to each other I’m able to think about myself in new ways. I’m able to see rather than just the fact that I started new blog I a funny goofy email I send out to friends I can see how that evolved and that came about and based on these feature in these graphs I can actually like understand more of like where my ideas come from and how they can change overtime. There’s a lot that can be done in Gephy that I haven’t even gotten to. But really like that one at TED those five seconds carried a much greater weight than just five seconds. I think the same can be true of ideas. You know, how do I remember what was new to me four years ago? How do I understand the ideas that I’m encountering today are influencing me as a function of time? You know I really wonder how I can discover more ways to think about myself and how I can kind of explore how my mind looks relative to other peoples. You know, I wonder if there are hidden patterns inside of this, and I don’t know the answers to these questions, but I think there are answers or can be. You know I am very curious to understand who I am and how I exist. Consciousness is my greatest curiosity and you know in the end we need to think that socially about how to better think about thinking. This was a momentous task to put all this together and it can be done certainly more efficiently. You know in the end you are extraordinary and your mind is exquisite. You, the things that you think about and that are important to you creates who you are and who you will become. So imagine how you might answer the question, what inspires you if you had a quantified mind in your cognitive tool kit.
About the presenter[edit | edit source]
Amy Robinson gave this talk.