The research investigates the way users interact with leading topics of the 2018 Hungarian
general election campaign on candidates’ Facebook pages. It expects that the prominent
(immigration, corruption) and campaign-related topics generate more user engagement, while
policy topics and mobilization content are less interacted. It also tests the theory of issue ownership
in relation with user engagement. These expectations are tested on a dataset that includes all
posts (38030 posts) posted by all candidates during the campaign (511 candidates). Topics
are identified by text mining methods. The study demonstrates that corruption, development
policy and campaign are highly engaged topics, while immigration was more interacted only on
opposition politicians’ pages since the followers of pro-government candidates engage less with
immigration-related content. The most surprising result is that a reversed issue ownership effect
can be detected since politicians are generally less successful with their own topics.