Framing Unionization on Facebook: Communication around Representation Elections in the United States

Arianna Pera, Veronica Jude, Ceren Budak, Luca Maria Aiello

公開日: 2025/10/2

Abstract

Digital media have become central to how labor unions communicate, organize, and sustain collective action. Yet little is known about how unions' online discourse relates to concrete outcomes such as representation elections. This study addresses the gap by combining National Labor Relations Board (NLRB) election data with 158k Facebook posts published by U.S. labor unions between 2015 and 2024. We focused on five discourse frames widely recognized in labor and social movement communication research: diagnostic (identifying problems), prognostic (proposing solutions), motivational (mobilizing action), community (emphasizing solidarity), and engagement (promoting interaction). Using a fine-tuned RoBERTa classifier, we systematically annotated unions' posts and analyzed patterns of frame usage around election events. Our findings showed that diagnostic and community frames dominated union communication overall, but that frame usage varied substantially across organizations. In election cases that unions won, communication leading up to the vote showed an increased use of diagnostic, prognostic, and community frames, followed by a reduction in prognostic and motivational framing after the event--patterns consistent with strategic preparation. By contrast, in lost election cases unions showed little adjustment in their communication, suggesting an absence of tailored communication strategies. By examining variation in message-level framing, the study highlights how communication strategies adapt to organizational contexts, contributing open tools and data and complementing prior research in understanding digital communication of unions and social movements.

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