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Online fake news can have noxious consequences. Social media platforms are experimenting with different interventions to curb fake news' spread, often employing them simultaneously. However, research investigating the interaction of these interventions is limited. Here, we use the heuristic‐systematic model of information processing (HSM) as a theoretical framework to jointly test two interventions against fake news that are implemented at scale by social media platforms: (1) adding warning labels from fact checkers to initiate systematic processing and (2) removing social endorsement cues (e.g., engagement counts) to reduce the influence of this heuristic cue. Moreover, we accounted for dispositions previously found to affect a person's response to fake news through motivated reasoning or cognitive style. An online experiment in Germany (N = 571) confirmed that warning labels reduced the perceived …