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    Arvind Narayanan

    arvindn.livejournal.com · Personal blog · on HN since 2008

    Arvind Narayanan, a computer scientist, wrote on this LiveJournal about data, privacy, web traffic quality, caffeine and startup topics.

    Visit blogHN submissions
    Data & VisualizationPrivacy & PolicyWriting & Thinking
    What HN says

    Commenters link it for a power-law-style data fit that kept working on new datasets, and for his analysis of low-quality StumbleUpon traffic.

    Stats for nerds
    17HN people shared it
    35linked in comments
    654story points
    Jul 2011last shared
    2008people per year2011

    Top posts on HN

    1. 1
      Why read books if we can’t remember what’s in them?
      1 person · 106 points · first shared 2012 · 71 comments on HN
    2. 2
      The calculus of caffeine consumption
      7 people · 86 points · first shared 2008 · 16 comments on HN
    3. 3
      Lessons from the failure of Livejournal: when not to listen to your users
      1 person · 72 points · first shared 2008 · 24 comments on HN
    4. 4
      Harvesting email addresses surreptitiously
      1 person · 68 points · first shared 2010 · 26 comments on HN
    5. 5
      Is Chess with Queen Odds a Provable Win?
      1 person · 52 points · first shared 2011 · 43 comments on HN
    6. 6
      Amazon is not the enemy
      1 person · 49 points · first shared 2009 · 65 comments on HN
    7. 7
      Thoughts on the Y Combinator interview process
      1 person · 43 points · first shared 2009 · 8 comments on HN
    8. 8
      The death of the printed book is closer than you think
      1 person · 33 points · first shared 2009 · 34 comments on HN
    9. 9
      The anatomy of a privacy meme
      1 person · 29 points · first shared 2010 · 2 comments on HN
    10. 10
      Why Craigslist needs to die
      1 person · 25 points · first shared 2009 · 25 comments on HN

    What HN people wrote when they linked it

    • lionheartedDec 2009

      If this sort of thing is fascinating to you, and you consume caffeine, you absolutely must spend the short time to learn about antagonistic and reinforcing caffeine usage. I've read a few papers on it, but I'm not finding any of the best ones by googling. This link has a short overview though:

      http://arvindn.livejournal.com/57651.html

      > What is common to these tasks is that progress happens in spurts, due to the fact that they involve frequent cognitive bottlenecks. A cognitive bottleneck can only be overcome when attention level exceeds a task dependent, typically very high threshold. Clearly, then, antagonistic caffeine consumption results in worse-than-normal productivity, because it flattens the attention level curve and decreases the fraction of time spent at peak attention level. Instead, reinforcing consumption helps maximize productivity (the red line). According to this strategy, the best time to drink coffee is when you are already very alert.

      Basically, caffeine gives you a boost, then withdrawal. If you're doing creative work, time your caffeine consumption to your high energy periods, then rest during the withdrawal. If you're doing rote, repetitious work, take caffeine during your low periods to smooth your energy out.

      This is incredible for your productivity, especially if you're doing creative work that you can't brute force yourself to finish. Highly recommended, almost should be mandatory for any anyone who consumes caffeine and does creative work.

    • bravuraDec 2010

      Honestly, this data should be free, and available to researchers who work on social tagging.

      You should contribute your bookmarks to a public data set. http://bulk.archive.org has offered to host such data sets.
      Someone should build a webservice that allows you to easily share your delicious tags. If no one steps up, you can simply email me your export (turian at gmail), and I'll package up whatever I receive.

      Here is a delicious data set, for those who are interested:
      http://arvindn.livejournal.com/116137.html

      I have some other social tagging datasets in my file. Let me know if you'd like me to dig them up.

    • lutormMar 2010

      An interesting and very different take on caffeine consumption strategy was posted here a while ago:

      http://arvindn.livejournal.com/57651.html

      The idea is that you should use caffeine when you're at your peak, because you want to maximize your productivity for doing really hard stuff that you normally would only accomplish when you're having a creative spurt anyway.

    • anotherJul 2011

      But what sort of traffic?

      See, e.g., Arvind's comments on StumbleUpon visitors:

      http://arvindn.livejournal.com/133249.html

      To quote the takeaway, "most of the traffic generated by StumbleUpon users to any given site is going to be low quality because the dopamine junkies make 100x more clicks".

    • randomwalkerDec 2008

      Man, this never gets old. Every time I see it work on a different dataset, it's as surprising as the first time I saw it. Recently I plotted supermodel incomes. It was an amazingly good fit. http://arvindn.livejournal.com/98510.html

    • abscondmentMar 2010

      Via coffee. Scratch that; via well-planned caffeine consumption: http://arvindn.livejournal.com/57651.html

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