Abstract

http://ssrn.com/abstract=1620401
 
 

References (42)



 
 

Citations (2)



 


 



Twitter Adoption in Congress


Feng Chi


University of Toronto - Rotman School of Management

Nathan Yang


Yale School of Management

March 29, 2010

Review of Network Economics, Vol. 10, No. 1

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 8 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.

Number of Pages in PDF File: 49

Keywords: Diffusion of technology, network effects, political marketing, social learning, social media.

JEL Classification: M3, D83, D85

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Date posted: June 5, 2010 ; Last revised: August 31, 2012

Suggested Citation

Chi, Feng and Yang, Nathan, Twitter Adoption in Congress (March 29, 2010). Review of Network Economics, Vol. 10, No. 1. Available at SSRN: http://ssrn.com/abstract=1620401

Contact Information

Feng Chi
University of Toronto - Rotman School of Management ( email )
105 St. George Street
Toronto, Ontario M5S 3E6
Canada
Nathan Yang (Contact Author)
Yale School of Management ( email )
135 Prospect Street
P.O. Box 208200
New Haven, CT 06520-8200
United States
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