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Twitter Adoption in Congress

Author

Listed:
  • Chi Feng

    (University of Toronto Rotman School of Management)

  • Yang Nathan

    (University of Toronto)

Abstract

We study the early adoption of Twitter in the 111th House of Representatives. Our main objective is to determine whether successes of past adopters have the tendency to speed up Twitter adoption, where past success is defined as the average followers per Tweet - a common measure of "Twitter success" - among all prior adopters. The data suggests that accelerated adoption can be associated with favorable past outcomes: increasing the average number of followers per Tweet among past adopters by a standard deviation (of eight followers per Tweet) accelerates the adoption time by about 112 days. This acceleration effect is weaker for those who already have adopted Facebook and those who have access to information about a large number of past adopters. We later find a positive relationship between an adopter's own success and the success of adopters preceding him/her. Thus, there may exist benefits associated with adopting Twitter based on past successes of others. In general, the patterns we find are consistent with predictions generated by a simple model of adoption delay with learning.

Suggested Citation

  • Chi Feng & Yang Nathan, 2011. "Twitter Adoption in Congress," Review of Network Economics, De Gruyter, vol. 10(1), pages 1-46, March.
    • Handle: RePEc:bpj:rneart:v:10:y:2011:i:1:n:3
    DOI: 10.2202/1446-9022.1255
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    3. Ho Yoon & Han Park, 2014. "Strategies affecting Twitter-based networking pattern of South Korean politicians: social network analysis and exponential random graph model," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(1), pages 409-423, January.
    4. Hollibaugh, Gary E. & Klingler, Jonathan & Ramey, Adam, 2015. "Tentative Decisions," IAST Working Papers 15-29, Institute for Advanced Study in Toulouse (IAST).
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    6. Gary E. Hollibaugh Jr. & Adam J. Ramey & Jonathan D. Klingler, 2018. "Welcome to the Machine: A Model of Legislator Personality and Communications Technology Adoption," SAGE Open, , vol. 8(3), pages 21582440188, September.
    7. Leticia Bode & Alexander Hanna & Junghwan Yang & Dhavan V. Shah, 2015. "Candidate Networks, Citizen Clusters, and Political Expression," The ANNALS of the American Academy of Political and Social Science, , vol. 659(1), pages 149-165, May.
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