At the nexus of big data and dispute resolution
A case study on conflict-related search data
Keywords:big data, dispute resolution, CDR, search analytics, Sentiment analysis
This paper presents findings from an ongoing project that has analysed over 225 million annual online conflict-related search queries to better understand the scope and scale of conflict in America. The frequency, location, sentimentality and timing of 52,203 unique conflict search terms were monitored for every US county. Analysis has revealed the public’s collective interests and conflict intensities within 225 distinct conflict contexts, many of which have cyclical trends that can inform resource development and deployment efforts. It has allowed for the creation of maps detailing where conflict arrests or avoids local populations. Finally, it has revealed new insights into how the public prioritises frames for their conflicts and their preferred resolutions. Creative integration of traditional and previously unaligned data, such as presented here, will change the dispute resolution field with regard to its understanding of the dispute resolution marketplace, the surfacing of opportunities to satisfy that market, and the ability to monitor the resulting impact of interventions from the personal to broad societal levels.
Brück, T., Justino, P., Verwimp, P. and Avdeenko, A. (2010) Identifying Conflict and Violence in Micro-Level Surveys. Discussion Paper No. 5067. Bonn: Institute for the Study of Labor. Retrieved on 10 October 2015 from http://ftp.iza.org/dp5067.pdf.
Charkoudian, L. (2005) A quantitative analysis of the effectiveness of community mediation in decreasing repeat police calls for service. Conflict Resolution Quarterly 23(1): 87–98. http://dx.doi.org/10.1002/crq.126
Chung, C. and Pennebaker, J. (2007) The psychological functions of function words. In K. Fiedler (ed.) Social Communication 343–59. New York: Psychology Press.
comScore (2015) comScore releases September 2015 US desktop search engine rankings. Retrieved on 10 October 2015 from www.comscore.com/Insights/Market-Rankings/comScore-Releases-September-2015-US-Desktop-Search-Engine-Rankings
Corbett, W. E. H. and Corbett, J. R. (2011). Community mediation in economic crisis: the reemergence of precarious sustainability. Nevada Law Journal 11(2): 469.
Corbett, X. (2015) First-person observations of youth-oriented conflict during play. Retrieved on 25 September 2015 from www.advancingdr.org/x#TOC-Play.
Economist (2010) Data, data everywhere: a special report on managing information. The Economist (25 February). Retrieved on 10 October 2015 from www.economist.com/node/15557443?story_ id=15557443.
Forbes, D. (2015) The Science of Why: Decoding Human Motivation and Transforming Marketing Strategy. New York: Palgrave Macmillan. http://dx.doi.org/10.1057/9781137502049
Foulk, T., Woolum, A. and Erez, A. (2015). Catching rudeness is like catching a cold: the contagion effects of low-intensity negative behaviors. Journal of Applied Psychology 101(1): 50–67. http://dx.doi.org/10.1037/apl0000037
Gaglio, C. M. and Katz, J. A. (2001) The psychological basis of opportunity identification: entrepreneurial alertness. Small Business Economics 16: 95–111. http://dx.doi.org/10.1023/A:1011132102464
Gardeazabal, J. (2012) Methods for measuring aggregate costs of conflict. In M. R. Garfinkel and S. Skaperdas (eds) The Oxford Handbook of the Economics of Peace and Conflict 227–51. Oxford: Oxford University Press. http://dx.doi.org/10.1093/oxfordhb/9780195392777.013.0011
Ginsberg, J., Mohebbi, M. H., Patel, R. S., Brammer, L, Smolinski, M. S. and Brilliant, L. (2009) Detecting influenza epidemics using search engine query data. Nature 457: 1012–14. http://dx.doi.org/10.1038/nature07634
Google (2015a) Google flu trends and Google dengue trends. Retrieved on 10 October 2015 from www.google.org/flutrends/about.
Google (2015b) Micro-Moments: Your Guide to Winning the Shift to Mobile. Mountain View, CA: Google. Retrieved on 10 October 2015 from https://think.storage.googleapis.com/images/micromoments-guide-to-winning-shift-to-mobile-download.pdf.
Google (2015c) TensorFlow: smarter machine learning, for everyone. Retrieved on 9 November 2015 from https://googleblog.blogspot.com/2015/11/tensorflow-smarter-machine-learning-for.html.
Hedeen, T. and Coy, P. G. (2000) Community mediation and the court system: the ties that bind. Mediation Quarterly 17(4): 351–67. http://dx.doi.org/10.1002/crq.3890170407
Hillis, K., Petit, M. and Jarrett, K. (2013) Google and the Culture of Search. New York: Routledge.
Institute for Economics and Peace (2015) Global Peace Index 2015: Measuring Peace, Its Causes and Its Economic Value. Sydney: Institute for Economics and Peace. Retrieved on 10 October 2015 from www.visionofhumanity.org/sites/default/files/Global%20Peace%20Index%20Report%202015_0.pdf.
Jaklevic, M. C. (2015) Where are STDs rampant? Google wants to help researchers find out. Kaiser Health News (10 December). Retrieved on 10 December 2015 from http://khn.org/news/where-are-stds-rampant-google-wants-to-help-researchers-find-out.
Jehn, K. A., Northcraft, G. B. and Neale, M. A. (1999) Why differences make a difference: a field study of diversity, conflict, and performance in workgroups. Administrative Science Quarterly 44(4): 741–63. http://dx.doi.org/10.2307/2667054
Kelling, G. L. and Wilson, J. Q. (1982) Broken windows: the police and neighborhood safety. The Atlantic (March). Retrieved on 10 October 2015 from www.theatlantic.com/magazine/archive/1982/03/broken-windows/304465.
Kim, K. E. (2015) Framing as a strategic persuasive message tactic. In D. Holtzhausen and A. Zerfass (eds) The Routledge Handbook of Strategic Communication 285–302. New York: Routledge.
Lawson, M. (2015) I-want-to-go moments: from search to store. Retrieved on 10 October 2015 from https://www.thinkwithgoogle.com/articles/i-want-to-go-micro-moments.html.
Lexalytics (2015) Sentiment Extraction: Measuring the Emotional Tone of Content. Boston, MA: Lexalytics. Retrieved on 10 October 2015 from www.lexalytics.com/content/whitepapers/Lexalytics-WP-Sentiment-Extraction.pdf.
Marchetti, H. and Jazbec, A. (2015) Getting stabbed by a unicorn. Hélice 4(2). Retrieved on 10 October 2015 from www.triplehelixassociation.org/helice/volume-4-2015/helice-issue-2-4/triple-helix-scientific-news/getting-stabbed-by-a-unicorn.
McGillis, D. (1997) Community Mediation Programs: Developments and Challenges. Washington, DC: National Institute of Justice.
McKinsey Global Institute (2011) Big data: the next frontier for innovation, competition, and productivity. Retrieved on 10 October 2015 from www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation?cm_mc_uid=21107781343814483157243&cm_mc_sid_50200000=1448315724.
Moses, L. B. and Chan, J. (2014) Using big data for legal and law enforcement decisions: testing new tools. UNSW Law Journal 37(2): 643–78.
Motorola (2015) 2015 Motorola global smartphone relationship survey. Retrieved on 10 October 2015 from http://motorola-blog.blogspot.com/2015/07/2015-motorola-global-smartphone.html.
O’Brien, D. T. and Sampson, R. J. (2015) Public and private spheres of neighborhood disorder: assessing pathways to violence using large-scale digital records. Journal of Research in Crime and Delinquency 52(4): 486–510. http://dx.doi.org/10.1177/0022427815577835
Pew Research Center (2012) The future of big data. Retrieved on 10 October 2015 from www.pewinternet.org/2012/07/20/main-findings-influence- of-big-data-in-2020.
Plous, S. (1993) The Psychology of Judgment and Decision Making. New York: McGraw-Hill Book Company.
Rule, C. (2015) Technology and the future of dispute resolution. Dispute Resolution Magazine 21(2). Retrieved on 10 October 2015 from www.americanbar.org/publications/dispute_resolution_magazine/2015/winter/technology-and-the-future-of-dispute-resolution.html.
Singhal, A. (2015) Interview statements made at code/mobile. Re/code (11 October). Retrieved on 11 October 2015 from http://recode.net/2015/10/11/googles-search-boss-talks-surviving-and-thriving-in-an-app-world-full-video.
Skogan, W. G., Hartnett, S. M., Bump, N. and Dubois, J. (2009) Evaluation of CeaseFire-Chicago. Chicago, IL: CeaseFire. Retrieved on 10 October 2015 from www.skogan.org/files/Evaluation_of_CeaseFire-Chicago_Main_Report.03-2009.pdf.
Soltas, E. and Stephens-Davidowitz, S. (2015) The rise of hate speech. New York Times (12 December). Retrieved on 12 December 2015 from www.nytimes.com/2015/12/13/opinion/sunday/the-rise-of-hate-search.html.
Stokoe, E. (2013) Overcoming barriers to mediation in intake calls to services: research-based strategies for mediators. Negotiation Journal 29(3): 289–314. http://dx.doi.org/10.1111/nejo.12026
Supreme Court of Nevada (2014) Rules of practice for the Eighth Judicial District Court of the State of Nevada, rule 5.07: seminar for separating parents. Retrieved on 10 October 2015 from www.leg.state.nv.us/courtrules/EighthDCR.html.
Varian, H. R. (2013) Beyond big data. Paper presented at the NABE Annual Meeting, 10 September, San Francisco, CA. Retrieved on 10 October 2015 from http://people.ischool.berkeley.edu/~hal/Papers/2013/BeyondBigDataPaperFINAL.pdf.
Velikonja, U. (2009) Making peace and making money: economic analysis of the market for mediators in private practice. Albany Law Review 72: 257–91.
Welch, Jr., J. F., Immelt, J. R., Dammerman, D. D. and Wright, R. C. (2001) To our customers, share owners and employees. In General Electric, GE Annual Report 2000 1–7. Fairfield, CT: General Electric Company. Retrieved on 10 October 2015 from www.ge.com/annual00/download/images/GEannual00.pdf.
Yang, S., Santillana, M. and Kou, S. C. (2015) Accurate estimation of influenza epidemics using Google search data via ARGO. Proceedings of the National Academy of Sciences 112(47): 14,473–8. http://dx.doi.org/10.1073/pnas
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