Why do people feel nostalgic for a former dictatorship? And through what means is authoritarian nostalgia delivered, circulated, and accepted to and by the mass? Nostalgic rhetoric for the fallen regime still shapes voters’ attitudes and related behavior in many post-authoritarian democracies, and we study what sort of messages are positively associated with nostalgic sentiments by examining digital trace data from Twitter. Leveraging the case of the Philippines presidential election in May 2022, we conduct text-as-data analysis at both individual-tweet and user-account levels, investigating the characteristics of nostalgia tweets and the types of voters who are more likely to post such tweets. We improve text classification by combining machine-based topic modeling and human-labeling and further conduct statistical inference with sentiment analysis. Combined results from this paper provide among the first empirical analysis of large-scale data on how voters discuss and distribute nostalgic rhetoric for a former dictatorship.