Abstract

ABSTRACT This study investigates the political topics that triggered user engagement on candidates’ Facebook pages during the 2018 Hungarian general election campaign on a full dataset of politicians’ communication by using automated content analysis approaches. We have limited knowledge on what topics spread well on Facebook. This study aims to fill this gap by investigating the engagement-triggering effects of prominent topics of the 2018 Hungarian election campaign. It hypothesizes that salient issues (immigration and corruption) and campaign-related posts will obtain more user reaction, while policy topics and mobilization-related content will be less engaging. The effects of issue ownership on user engagement are also tested. For this, the study draws upon an extensive dataset that includes all Facebook posts of each candidate (511 candidates 38030 posts) running for MP positions, posted between the official starting day of the campaign and Election Day. Topics are identified by dictionary-based and supervised learning methods that allow us to categorize a larger set of data than earlier works. The results show that corruption, development policy, and campaign are the most popular topics with users. The most interesting finding, however, is related to the reversed issue ownership effect on user engagement.

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