Literature DB >> 29235916

Harvesting Social Signals to Inform Peace Processes Implementation and Monitoring.

Aastha Nigam1,2, Henry K Dambanemuya2,3, Madhav Joshi3, Nitesh V Chawla1,2,3.   

Abstract

Peace processes are complex, protracted, and contentious involving significant bargaining and compromising among various societal and political stakeholders. In civil war terminations, it is pertinent to measure the pulse of the nation to ensure that the peace process is responsive to citizens' concerns. Social media yields tremendous power as a tool for dialogue, debate, organization, and mobilization, thereby adding more complexity to the peace process. Using Colombia's final peace agreement and national referendum as a case study, we investigate the influence of two important indicators: intergroup polarization and public sentiment toward the peace process. We present a detailed linguistic analysis to detect intergroup polarization and a predictive model that leverages Tweet structure, content, and user-based features to predict public sentiment toward the Colombian peace process. We demonstrate that had proaccord stakeholders leveraged public opinion from social media, the outcome of the Colombian referendum could have been different.

Entities:  

Keywords:  Colombia; big data analytics; data mining; machine learning; peace process; predictive analytics; social media

Mesh:

Year:  2017        PMID: 29235916      PMCID: PMC5734239          DOI: 10.1089/big.2017.0055

Source DB:  PubMed          Journal:  Big Data        ISSN: 2167-6461            Impact factor:   2.128


  3 in total

1.  Knowing what to think by knowing who you are: self-categorization and the nature of norm formation, conformity and group polarization.

Authors:  D Abrams; M Wetherell; S Cochrane; M A Hogg; J C Turner
Journal:  Br J Soc Psychol       Date:  1990-06

Review 2.  Predicting armed conflict: Time to adjust our expectations?

Authors:  Lars-Erik Cederman; Nils B Weidmann
Journal:  Science       Date:  2017-02-02       Impact factor: 47.728

3.  A 61-million-person experiment in social influence and political mobilization.

Authors:  Robert M Bond; Christopher J Fariss; Jason J Jones; Adam D I Kramer; Cameron Marlow; Jaime E Settle; James H Fowler
Journal:  Nature       Date:  2012-09-13       Impact factor: 49.962

  3 in total

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