Twitter Adoption in Congress
Chi Feng and
Nathan Yang ()
Additional contact information
Chi Feng: University of Toronto Rotman School of Management
Review of Network Economics, 2011, vol. 10, issue 1, 46
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.
Keywords: diffusion of technology; network effects; political marketing; social learning; social media (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)
Downloads: (external link)
https://doi.org/10.2202/1446-9022.1255 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bpj:rneart:v:10:y:2011:i:1:n:3
Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/rne/html
DOI: 10.2202/1446-9022.1255
Access Statistics for this article
Review of Network Economics is currently edited by Lukasz Grzybowski
More articles in Review of Network Economics from De Gruyter
Bibliographic data for series maintained by Peter Golla ().