845
Views
7
CrossRef citations to date
0
Altmetric
Articles

Comparing organizational content and fan interaction on Twitter and Facebook in United States professional sport

, , &
Pages 358-375 | Received 20 Jun 2018, Accepted 08 Jan 2020, Published online: 10 Feb 2020
 

ABSTRACT

Rationale/Purpose: The purpose of this study was to extend social media research by comparing how professional sport organizations in the United States used Facebook and Twitter in the off-season and how interaction on these networks differs. Design/Methodology/Approach: Data were collected from professional sport teams’ Facebook and Twitter pages and deductive content analysis was used. Interaction data were then analyzed using multivariate multilevel modeling. Findings: Results suggested both networks were used most often for player and personnel promotion, and fans interacted most often with this content. However, Twitter was used more for information dissemination and Facebook was used more for organizational promotion. Overall, interaction on Facebook was significantly greater than interaction on Twitter. Practical Implications: Sport marketers and researchers can utilize these results to make strategic content plans to effectively engage fans. Research Contribution: This study used statistical modeling to compare and test differences between networks and focused on off-season content.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This project was funded by a University Research Grant at Illinois State University.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 689.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.