Analyzing Candidates' Ideological Messaging Throughout the Electoral Cycle

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Abstract/Contents

Abstract: Conventional wisdom suggests that primary elections attract a loyal base of partisans, and consequently, political candidates must take more extreme positions to secure the nomination before moderating for the general electorate. Yet, the academic literature contains little empirical evidence on candidate positioning over the electoral process. I address this gap by using congressional candidates' tweets to quantify ideological rhetoric during the 2020 election using three different approaches. First, I adopt a data-driven approach to select the most partisan bigrams and specify a multinomial model of speech; second, I use a theoretically-derived dictionary to measure the frequency of moral values associated with political convictions; finally, I specify a natural language model using a deep learning architecture. I provide one of the first empirical analyses on the evolution of candidates' ideological messaging over the entire election cycle. I find statistically significant evidence of moderation among Republican but not Democratic candidates, with mixed support for greater movement in competitive general elections. I conclude that Republicans likely face stronger incentives than Democrats to employ extreme rhetoric in primaries and thus to moderate in general elections.

Author	Wittenbrink, Benjamin
Thesis advisor	Gentzkow, Matthew

Subject	Machine Learning
Subject	Social Media
Subject	Stanford University Department of Economics
Subject	Political Communication
Subject	Ideology
Subject	Elections
Subject	Text Analysis
Subject	Political Economy
Genre	Text
Genre	Thesis

DOI	https://doi.org/10.25740/tg119qr1168
Location	https://purl.stanford.edu/tg119qr1168

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License: This work is licensed under a Creative Commons Attribution Non Commercial 4.0 International license (CC BY-NC).

Preferred citation: Wittenbrink, B. (2022). Analyzing Candidates' Ideological Messaging Throughout the Electoral Cycle. Stanford Digital Repository. Available at https://purl.stanford.edu/tg119qr1168

Stanford University, Department of Economics, Honors Theses

Contact: witten@stanford.edu; witten@cs.stanford.edu; bhwittenbrink@gmail.com

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