Honors Theses

Advisor

Daniel Birdsong

Department

Political Science

Publication Date

4-26-2020

Document Type

Honors Thesis

Abstract

Social media have become a primary vehicle through which interest groups have sought influence on the U.S. political system. While the relationship between social media and politics has been studied, little research has been conducted into which posts, specifically from interest groups, receive the most public feedback. Through a content analysis, I coded more than 2,000 tweets from two pairs of diametrically opposed interest groups according to the type of language that was employed in the tweet (argumentative, agreeable, action-oriented) and the multimedia that was utilized (plain, photo, link, video). Tweets with argumentative language tended to receive more likes, retweets, and replies than tweets without argumentative language. Additionally, linear regression analysis showed there were statistically significant positive relationships between retweets and argumentative language and replies and argumentative language. The positive statistically significant relationship between retweets and argumentative language persisted when the data was disaggregated by organization. Tweets with video tended to receive more public feedback than tweets without video. Multivariable linear regression analysis showed that a tweet’s inclusion of video had a larger impact on its likelihood of receiving more public feedback than its inclusion of argumentative language. The implication of this is that future research should consider the related influences that multiple variables have on a tweet’s success in receiving public feedback.

Permission Statement

This item is protected by copyright law (Title 17, U.S. Code) and may only be used for noncommercial, educational, and scholarly purposes.


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