IDEAS home Printed from https://ideas.repec.org/a/eee/eejocm/v17y2015icp28-38.html
   My bibliography  Save this article

Social network influence on consistent choice

Author

Listed:
  • Reed, Markum

Abstract

Social networks tend to shape our view about the world. Our study conducts and empirical analysis of social network dynamics using Twitter data. We ask whether social networks influence voting decisions, and determine whether or not people make consistent choice based on their tweets. We collect Twitter data on a daily basis, with dynamic social network measurements before, during, and after the 2012 Presidential election. We use lexicographical analysis to check if ideological keywords are present in a user's tweets, and if the overall sentiment on this issue is positive or negative. We utilize this data to determine how people should have chosen an outcome, which may conflict with an individual's observed declaration of political ideology. We are able to determine what percentage of the population made a consistent choice based on their Tweets during the 2012 presidential election. Additionally, we examine the social network structure in Twitter and how it affects voting. We illustrate that an individual's political ideology is influenced by their network.

Suggested Citation

  • Reed, Markum, 2015. "Social network influence on consistent choice," Journal of choice modelling, Elsevier, vol. 17(C), pages 28-38.
    • Handle: RePEc:eee:eejocm:v:17:y:2015:i:c:p:28-38
    DOI: 10.1016/j.jocm.2015.12.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1755534515301172
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jocm.2015.12.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gilens, Martin, 2001. "Political Ignorance and Collective Policy Preferences," American Political Science Review, Cambridge University Press, vol. 95(2), pages 379-396, June.
    2. Althaus, Scott L., 1998. "Information Effects in Collective Preferences," American Political Science Review, Cambridge University Press, vol. 92(3), pages 545-558, September.
    3. Watts, Alison, 2014. "The influence of social networks and homophily on correct voting," Network Science, Cambridge University Press, vol. 2(1), pages 90-106, April.
    4. Lau, Richard R. & Redlawsk, David P., 1997. "Voting Correctly," American Political Science Review, Cambridge University Press, vol. 91(3), pages 585-598, September.
    5. Stanley Wasserman & Philippa Pattison, 1996. "Logit models and logistic regressions for social networks: I. An introduction to Markov graphs andp," Psychometrika, Springer;The Psychometric Society, vol. 61(3), pages 401-425, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mei Cai & Li Yan & Zaiwu Gong & Guo Wei, 2021. "A Voting Mechanism Designed for Talent Shows in Mass Media: Weighted Preference of Group Decision Makers in Social Networks Using Fuzzy Measures and Choquet Integral," Group Decision and Negotiation, Springer, vol. 30(6), pages 1261-1284, December.
    2. Pink, Sebastian & Kretschmer, David & Leszczensky, Lars, 2020. "Choice modelling in social networks using stochastic actor-oriented models," Journal of choice modelling, Elsevier, vol. 34(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Matthew L. Bergbower & Scott D. McClurg & Thomas Holbrook, 2015. "Presidential Campaign Spending and Correct Voting from 2000 to 2008," Social Science Quarterly, Southwestern Social Science Association, vol. 96(5), pages 1196-1213, November.
    2. James Tilley & Christopher Wlezien, 2008. "Does Political Information Matter? An Experimental Test Relating to Party Positions on Europe," Political Studies, Political Studies Association, vol. 56(1), pages 192-214, March.
    3. Jo Thori Lind & Dominic Rohner, 2017. "Knowledge is Power: A Theory of Information, Income and Welfare Spending," Economica, London School of Economics and Political Science, vol. 84(336), pages 611-646, October.
    4. Matt Guardino & Suzanne Mettler, 2020. "Revealing the “Hidden welfare state†: How policy information influences public attitudes about tax expenditures," Journal of Behavioral Public Administration, Center for Experimental and Behavioral Public Administration, vol. 3(1).
    5. Kim, Jaehoon & Fey, Mark, 2007. "The swing voter's curse with adversarial preferences," Journal of Economic Theory, Elsevier, vol. 135(1), pages 236-252, July.
    6. Nicholas Clark & Timothy Hellwig, 2012. "Information effects and mass support for EU policy control," European Union Politics, , vol. 13(4), pages 535-557, December.
    7. Katharina Werner, 2019. "The Role of Information for Public Preferences on Education – Evidence from Representative Survey Experiments," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 82.
    8. Sara B Hobolt & Sebastian Adrian Popa & Wouter Van der Brug & Hermann Schmitt, 2022. "The Brexit deterrent? How member state exit shapes public support for the European Union," European Union Politics, , vol. 23(1), pages 100-119, March.
    9. Nordin, Mattias, 2015. "Local Television, Citizen Knowledge and Political Accountability: Evidence from the U.S. Senate," Working Paper Series 2015:5, Uppsala University, Department of Economics.
    10. Ganzach, Yoav, 2018. "Intelligence and the rationality of political preferences," Intelligence, Elsevier, vol. 69(C), pages 59-70.
    11. Brendan Nyhan, 2011. "The limited effects of testimony on political persuasion," Public Choice, Springer, vol. 148(3), pages 283-312, September.
    12. Jason Barabas, 1998. "Wage Erosion, Economic Assessments, and Social Welfare Opinions," JCPR Working Papers 56, Northwestern University/University of Chicago Joint Center for Poverty Research.
    13. Manuel E. Sosa & Steven D. Eppinger & Craig M. Rowles, 2004. "The Misalignment of Product Architecture and Organizational Structure in Complex Product Development," Management Science, INFORMS, vol. 50(12), pages 1674-1689, December.
    14. Thompson, Paul N., 2019. "Are school officials held accountable for fiscal stress? Evidence from school district financial intervention systems," Economics of Education Review, Elsevier, vol. 72(C), pages 44-54.
    15. Cilem Selin Hazir & Corinne Autant-Bernard, 2012. "Using Affiliation Networks to Study the Determinants of Multilateral Research Cooperation Some empirical evidence from EU Framework Programs in biotechnology," Working Papers 1212, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    16. Lergetporer, Philipp & Schwerdt, Guido & Werner, Katharina & West, Martin R. & Woessmann, Ludger, 2018. "How information affects support for education spending: Evidence from survey experiments in Germany and the United States," Journal of Public Economics, Elsevier, vol. 167(C), pages 138-157.
    17. Samrachana Adhikari & Beau Dabbs, 2018. "Social Network Analysis in R: A Software Review," Journal of Educational and Behavioral Statistics, , vol. 43(2), pages 225-253, April.
    18. John Patty & Roberto Weber, 2007. "Letting the good times roll: A theory of voter inference and experimental evidence," Public Choice, Springer, vol. 130(3), pages 293-310, March.
    19. Calvin Thigpen & Kelcie Ralph & Nicholas J. Klein & Anne Brown, 2023. "Can information increase support for transportation reform? Results from an experiment," Transportation, Springer, vol. 50(3), pages 893-912, June.
    20. David Levinson & Arthur Huang, 2012. "A Positive Theory of Network Connectivity," Environment and Planning B, , vol. 39(2), pages 308-325, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eejocm:v:17:y:2015:i:c:p:28-38. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/journal-of-choice-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.