***** To join INSNA, visit http://www.insna.org *****
David Nickerson had a clever field experiment examining contagion of
turnout. Essentially, the treatment was to knock on doors of two voter
households, give a get out the vote pitch to the individual who answered the
door, and to see if the _other_ person was more likely to vote (this was
compared to a placebo group of alters who received an unrelated pitch
regarding recycling). Nickerson found quite a substantial contagion effect
(about 60% the size of the impact of receiving the get out the vote pitch
directly).
dl
Nickerson, David W. 2008. "Is Voting Contagious? Evidence from Two Field
Experiments," *American Political Science Review*
102(Feb):49-57.<http://www.nd.edu/~dnickers/papers/nickerson.contagion.pdf>
<http://www.nd.edu/~dnickers/papers/nickerson.contagion.pdf>
http://www.nd.edu/~dnickers/papers/nickerson.contagion.pdf
David Lazer (www.davidlazer.com)
Associate Professor of Political Science and Computer Science
Northeastern University &
Director, Program on Networked Governance
Harvard Kennedy School
Harvard University
The netgov blog: http://www.iq.harvard.edu/blog/netgov/
On Sun, Feb 27, 2011 at 4:23 AM, Thomas Valente <[log in to unmask]> wrote:
> ***** To join INSNA, visit http://www.insna.org *****
>
> Sinan
>
> I agree, experiments are great when you can do them and we have 2 published
> RCTs that I think demonstrate contagion effects.
>
>
>
> Valente, T. W*.*, Hoffman, B. R., Ritt-Olson, A., Lichtman, K., & Johnson,
> C. A. (2003). The effects of a social network method for group assignment
> strategies on peer led tobacco prevention programs in schools. *American
> Journal of Public Health*, *93*, 1837-1843.
>
>
>
> Valente, T. W., Ritt-Olson, A., Unger, J., Stacy, A., Okamoto, J. &
> Sussman, S., (2007). Peer acceleration: Effects of a network tailored
> substance abuse prevention program among high risk adolescents. *
> Addiction*, *102*, 1804-1815.
>
>
>
> - Tom
>
>
>
> *From:* Social Networks Discussion Forum
>
> [mailto:[log in to unmask]] *On Behalf Of *Sinan Aral
> *Sent:* Saturday, February 26, 2011 11:03 PM
>
> *To:* [log in to unmask]
> *Subject:* Re: Measuring contagion in longitudinal behavior data
>
>
>
> ***** To join INSNA, visit http://www.insna.org *****
>
> Steve,
>
> We have been working on this problem as well. In my opinion, the cleanest
> and most reliable way to estimate social contagion or peer effects in
> networks is through a randomized trial (see the first paper below, which is
> to our knowledge the largest randomized trial of social contagion conducted
> to date). You might find the other follow papers interesting as well as they
> pertain directly to estimating contagion effects. In the first two papers
> there are literature reviews of various prior approaches. The second paper
> listed is my comment on Tom's excellent paper with Christophe and Ragu ("Opinion
> leadership and contagion in new product diffusion") which discusses the
> theories and methods estimating contagion effects in some detail... it is
> also in press at Marketing Science. Hope these help!
>
> Best
>
> Sinan
>
> Aral, S. & Walker, D. (Forthcoming) “Creating Social Contagion through
> Viral Product Design: A Randomized Trial of Peer Influence in Networks.” *Management
> Science*. (conditionally accepted pending minor revisions).
>
> http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1564856
>
>
> Aral, S. (in press). “Identifying Social Influence: A Comment on Opinion
> Leadership and Social Contagion in New Product Diffusion.” *Marketing
> Science*.
>
> http://mktsci.journal.informs.org/cgi/reprint/mksc.1100.0596v1
>
>
> Aral, S., Muchnik, L., & Sundararajan, A. 2009. “Distinguishing Influence
> Based Contagion from Homophily Driven Diffusion in Dynamic Networks,” *Proceedings
> of the National Academy of Sciences*, Dec. 22, 2009, vol. 106, no.51.
>
> http://www.pnas.org/content/early/2009/12/09/0908800106.full.pdf
>
>
>
>
> Sinan Aral
>
> Assistant Professor, NYU Stern School of Business.
>
> Research Affiliate, MIT Sloan School of Management.
>
> Personal Webpage: http://pages.stern.nyu.edu/~saral
>
> SSRN Page: http://ssrn.com/author=110270
>
> WIN Workshop: http://www.winworkshop.net
>
> Twitter: http://twitter.com/sinanaral
>
>
> On 2/26/2011 4:00 AM, Thomas Valente wrote:
>
> ***** To join INSNA, visit http://www.insna.org *****
>
> Steve
>
>
>
> The Strange & Tuma 1993 article in AJS calculated 2 terms, infection:
> calculated as the number of ego’s alters that adopted an innovation after
> ego in the next time period after ego adopted; and susceptibility calculated
> as the adoption of ego after his alter adopts. Myers discussed these as
> well in a paper on collective violence. I also introduced a term I called
> the critical mass (in my 1995 book) which was adoption weighted by the
> outdegree of the egos. These are also discussed in the 2005 chapter models
> and methods for diffusion and somewhat in my latest book “Social Networks
> and Health.” At the macro level you can also calculate rate of diffusion
> using curve fitting techniques as discussed in my 1993 paper, covered very
> well by Mahajan & Peterson (1985). (And don’t forget the classic Bass
> (1969) model.) Of course the best way to estimate contagion is by using the
> autoregressive model which is discussed in my 2005 chapter and 2010 book.
> There are debates about the statistical validity of this approach but it
> is quite versatile and statistical limitations seem to be getting worked
> out. The latest example, to my knowledge, is the Iyengar et al. paper due
> out in Marketing Science.
>
>
>
> Bass, F. M. (1969). A new product growth model for consumer durables. *Management
> Science*, *15*, 215-227.Sage.
>
>
>
> Iyengar, R., Van den Bulte, C.* *& Valente, T. W.* *(in press). Opinion leadership and contagion in new product diffusion. *Marketing Science*.
>
>
>
> Mahajan, V., & Peterson, R. A. (1985). *Models of innovation diffusion*.
> Newbury Park, CA.
>
>
>
> Myers, D. J. (2000). The diffusion of collective violence: Infectiousness,
> susceptibility, and mass media networks. *American Journal of Sociology*,
> *106*, 173-208.
>
>
>
> Strang, D., & Tuma, N. B. (1993). Spatial and temporal heterogeneity in
> diffusion. *American Journal of Sociology*, *99*, 614-639.
>
>
>
> Valente, T. W. (1993). Diffusion of innovations and policy
> decision-making. *Journal of Communication*, *43*, 30-41.
>
>
>
> Valente, T. W. (1995). *Network models of the diffusion of innovations*.
> Cresskill, NJ: Hampton Press.
>
>
>
> Valente, T. W. (2005). Models and methods for innovation diffusion. In P.
> J. Carrington, J. Scott, & S. Wasserman (Eds.) *Models and methods in
> social network analysis*. Cambridge, UK: Cambridge University Press.
>
>
>
> Valente, T. W. (2005). Social Networks and Health: Models Methods and
> Applications. New York: Oxford University Press.
>
>
>
>
>
> -Tom
>
>
>
> Thomas W. Valente, PhD
>
> Current: École des hautes études en santé publique (Rennes/Paris, France)
>
> Usual:
>
> Director, Master of Public Health Program
> http://www.usc.edu/medicine/mph/
>
> Professor, Department of Preventive Medicine
>
> Keck School of Medicine
>
> University of Southern California
>
> 1000 S. Fremont Ave., #8
>
> Building A Room 5133
>
> Alhambra CA 91803
>
> phone: (626) 457-4139; cell: (626) 429-4123
>
> email: [log in to unmask]
>
>
>
> *Social Networks and Health: Models, Methods, and Applications*:
>
> http://www.oup.com/us (promo code: 28569)
>
> *Evaluating Health Promotion Programs*: www.oup-usa.org/
>
> *Network Models of the Diffusion of Innovations*: www.hamptonpress.com
>
> My personal webpage: http://www-hsc.usc.edu/~tvalente/
>
> The Empirical Networks Project: http://ipr1.hsc.usc.edu/networks/
>
> You Tube video on Diffusion of Innovations:
> http://www.youtube.com/watch?v=ZG9dAIBd4xQ
>
>
>
> *From:* Social Networks Discussion Forum [mailto:[log in to unmask]<[log in to unmask]>]
> *On Behalf Of *Steve Eichert
> *Sent:* Friday, February 25, 2011 8:29 PM
> *To:* [log in to unmask]
> *Subject:* Measuring contagion in longitudinal behavior data
>
>
>
> ***** To join INSNA, visit http://www.insna.org ***** Hello SOCNET,
>
>
>
> I'm looking for books, papers, algorithms, and/or ideas on how best to
> measure contagion in a network. We have longitudinal behavior data for all
> actors in a directed network and want to calculate the degree of contagion
> occurring between all connected nodes. We would like to use the calculated
> "contagion score" to identify nodes that we can do further analysis on, as
> well as to measure the overall level of contagion in the network. The
> longitudinal behavior data we have indicates how much of something the nodes
> within the network are using over time. We're interested in better
> understanding the algorithms folks are using for "adoption contagion"
> (someone who has already adopted influences a non adopter to adopt) as well
> as "behavior contagion" (a high user influences those connected to them to
> use more).
>
>
>
> Thoughts?
>
>
>
> Thanks,
> Steve
>
> _____________________________________________________________________
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>
> _____________________________________________________________________
> SOCNET is a service of INSNA, the professional association for social
> network researchers (http://www.insna.org). To unsubscribe, send an email
> message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET
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>
> _____________________________________________________________________
> SOCNET is a service of INSNA, the professional association for social
> network researchers (http://www.insna.org). To unsubscribe, send an email
> message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET
> in the body of the message.
> _____________________________________________________________________
> SOCNET is a service of INSNA, the professional association for social
> network researchers (http://www.insna.org). To unsubscribe, send an email
> message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET
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