Doug -

Yep, although who's to say that an onslaught of Nyquil twittertizing does not signify the beginning of a flu outbreak?
Righto! That is the point... how to distinguish a rash of NyQuil fanbois extolling it's virtues in 140 chars or less as they subdue early symptoms of a resurging 1918 Influenza outbreak from a catchy jingle P&G/Vicks/NyQuil's latest admen thought up?

Again, I'm not sure of the context of your hackathon (by it's name, it seems more like teambuilding/demonstration than seriously attacking a known/well-vetted problem?) but maybe there was talk of precedent... of more serious studies in how to find useful correlations?

I'd expect careful study would reveal a phased rollout of terms... that people mutter (twitter?) about different things at the onset of their own symptoms or of those around them than they do as it becomes a full-fledged experience ( e.g. Achy, Sniffly, Congested vs "Sick Day"). And of course there might be an abrupt *rise* or *fall* in tweet frequencies from the same people as they take a day off from work and/or switch from DayQuil to NyQuil and try to sleep it off.

Also, the seriousness of symptoms might be reflected in Google Trends, of people doing "research" as opposed to just mumble-tweeting about it.

- Steve

--Doug

On Mon, Mar 4, 2013 at 7:40 PM, Steve Smith <sasm...@swcp.com <mailto:sasm...@swcp.com>> wrote:



    It also seems as if subtracting news items might be important (for
    your purposes) since I assume you are looking for early detection
    of people having these symptoms rather than the echoes of trends
    in popular media (or an advertising push by NyQuil) ?


    Doug -

    So the point is to attempt "early detection" of an outbreak of
    something  based on what people are tweeting?

        ( "influenza", "flu", "cold", "fever", "H1N1", "H3N2",
        "sneezing", "aching", "ache", "achy", "congested" )

    It certainly sounds like there might be some utility to it, but
    I'm wondering what kinds of reasoning went into this?  Is it
    based on any models of who tweets or what they are likely to
    tweet about?

    Was it more of a demonstration or team-building exercise, or does
    someone expect to actually put it to use?

    So, the data was pre-archived, but I presume a more useful
    version would work from more real-time data and probably would
    have a sliding time (exponential moving average?) window?

    Do you know about Norm Packard's (ofEudaimonic, Prediction,
    ProtoLife <http://en.wikipedia.org/wiki/Norman_Packard> fame)
    latest venture called LuckySort <http://luckysort.com/>? It's R
    interface is called TopicWatchr
    <http://luckysort.com/products/r-package> and seems to be doing
something roughly similar (but without specific geolocation?). Their examples suggest that they are aiming this at the
    Investment sector.

    Our own Mick Thompson (well, SFX if not FRIAM) was working on
    related things before the startup Collecta went dark...  I'm not
    sure if he's still in this game (or on this list?).   I used
    Collecta when it was alive... it aggregated Twitter as well as
    some subset of blog and maybe newsfeeds?    For example, stuck in
    northbound traffic on I-25 near La Cienega one time, I was able
    to discover within seconds of stopping my vehicle that 3 people
    also stuck in traffic had mentioned that they too were stuck and
    one of them was close enough to the front of the line to see that
    it was a fuel truck that had been involved in an accident so they
    weren't inclined to let anyone past it until the HazMat or Fire
    folks had determined there was no risk.   On the other hand a CB
    Radio and/or a Police Scanner (oldschool) would have told me all
    that and more in time to take the La Cienega exit and frontage on
    into town with only a minor delay.



    One of my projects is funded by NIH, and it sponsored (read:
    paid for) a group of 15 of us software developer types from 10
    different organizations across the country who are working on
    the project to get together last week in Las Vegas, NV to
    conduct a two-day hackathon. We split into three groups, and my
    group produced some rough, ugly, but working Python and R code.

    The Python code conducts keyword searches on archived 1% Twitter
    API data, filtered to only search  only those tweets that have
    valid geolocation data. The short piece of R code calls a Google
    map API and plots the data on a Google map in a browser,
    allowing the user to click on the geolocated map points to view
    the originator's tweet text.

    Our next step will be to replace the R code with Python for
    calling the Google map API.

    Here, it's ugly, but it's free.  Don't say I never gave you
    anything.

    --Doug

-- /Doug Roberts
    d...@parrot-farm.net <mailto:d...@parrot-farm.net>/
    /http://parrot-farm.net/Second-Cousins/
    /
    505-455-7333 <tel:505-455-7333> - Office
    505-672-8213 <tel:505-672-8213> - Mobile/


    ============================================================
    FRIAM Applied Complexity Group listserv
    Meets Fridays 9a-11:30 at cafe at St. John's College
    to unsubscribehttp://redfish.com/mailman/listinfo/friam_redfish.com



    ============================================================
    FRIAM Applied Complexity Group listserv
    Meets Fridays 9a-11:30 at cafe at St. John's College
    to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com




--
/Doug Roberts
d...@parrot-farm.net <mailto:d...@parrot-farm.net>/
/http://parrot-farm.net/Second-Cousins/
/
505-455-7333 - Office
505-672-8213 - Mobile/


============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com

Reply via email to