NY Quantified Self Show&Tell #26 - Using Facebook for Health Insights
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My journey deriving health insights through self-visualization using Facebook data and beyond, presented for NY Quantified Self Show&Tell #26 on September 24th, 2014
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NY Quantified Self Show&Tell #26 - Using Facebook for Health Insights
- 1. Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2009 2010 2011 2012 2013 2014 Using For Health Insights Shawn Dimantha @sdimantha shawn@enfluence.io
- 2. I wanted to find a better way to keep track of my health without the hassle
- 3. MIT’s Immersion visualized my email network…
- 4. Why not use Facebook analytics? • Largest quantity and variety of data available • High quality images available • Could images be a window into my health?
- 5. An image is worth a thousand words insights
- 6. Published academic research supports this approach
- 7. A rating over time could help me forecast and track my health Off Track >2.2 Caution >2.1 to <2.2 Good < 2.1
- 8. 2009 2.26 2.24 2.26 2.31 2.18 2.22 2.26 2.31 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
- 9. 2010 2.16 2.27 2.23 2.03 2.16 2.13 2.12 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Commuting Princeton – NYC every day Joined local gym
- 10. 2011 2.32 2.39 2.39 2.4 2.26 2.16 2.31 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Commuting Princeton – NYC every day
- 11. 2012 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 70 day gym streak 2.25 2.15 2.21 2.04 2.07 2.24 2.18 2.2 Commuting Princeton – NYC every day
- 12. 2013 2.19 2.01 2.06 2.1 1.99 2.01 2.16 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Surgery + recovery Climbed Mt. Kilimanjaro
- 13. 2014 1.94 2.04 2.05 2.14 2.06 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec New job Trip home + 2 weddings / bachelor parties
- 14. Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2009 2010 2011 2012 2013 2014
- 15. What I learned • Facial image data needs to be cleaned and carefully selected. Face shapes are unique and need to be treated as such. • Data that is not present is often more telling than what is present • Life events effect my weight and should be put into context; however causation is harder to determine than correlation • By being more conscious of my score and I can change my behavior before things get off track
- 16. What would you include in a health score? Want to give it a try? shawn@enfluence.io @sdimantha
Editor's Notes
- 1.76/0.96 = 1.8 1.8/0.78 = 2.3
- Jan = 2.6/1.15 –> 2.26 Feb = 2.8/1.25 -> 2.24 Mar = 2.8/1.24 -> 2.26 Apr = 2.49/1.08 -> 2.31 May = 2.09/0.96 -> 2.18 Jul = 3.15/1.42= 2.22 Sep = 3.67/1.62 = 2.26 Dec = 2.79/1.21 = 2.31 July – 2.19 = 2.85/1.3 Sept – 2.25 = 4.05/1.85
- Jan: 2.36/1.09 = 2.16 Feb: 3.02/1.33 = 2.27 Apr: 2.52/1.13 = 2.23 May: N/A Jun: 2.75/1.35 = 2.03 Jul: 2.56/1.16 = 2.16 Aug: 2.24/1.05 = 2.13 Sep: N/A Oct: 2.16/1.02 = 2.12
- Jan: 2.88/1.24 = 2.32 Mar: 2.61/1.09 = 2.39 May: 2.44/1.02 = 2.39 Jun: 2.16/0.9 = 2.4 Jul: 2.76/1.22 = 2.26 Aug: 2.89/1.34 = 2.16 Sep: 3.21/1.39 = 2.31
- Apr: 3.39/1.51 = 2.25 May: 2.19/1.02 = 2.15 Aug: 3.27/1.6 = 2.04 Sep: 2.94/1.42 = 2.07 Oct: 2.91/1.3 = 2.24 Nov: 2.83/1.3 = 2.18 Dec: 2.86/1.3 = 2.2
- Jan: 2.94/1.34 = 2.19 Feb: 2.52/1.25 = 2.01 Mar: 2.52/1.22 = 2.06 May: 3.03/1.44 = 2.10 Jul: 2.86/1.44 = 1.99 Aug: 2.69/1.34 = 2.01 Oct: N/A Dec: 2.68 /1.24 = 2.16
- Feb: 3.09/1.59 = 1.94 Mar: 1.71/0.84 = 2.04 Apr 2.77/1.35 = 2.05 Aug 2.89/1.35 = 2.14 Sep 3.86/1.87 = 2.06