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

Fuente: arXiv
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Autori principali: Pera, Arianna, Jude, Veronica, Budak, Ceren, Aiello, Luca Maria
Natura: Preprint
Pubblicazione: 2025
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author Pera, Arianna
Jude, Veronica
Budak, Ceren
Aiello, Luca Maria
author_facet Pera, Arianna
Jude, Veronica
Budak, Ceren
Aiello, Luca Maria
contents 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 social media 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. Greater use of diagnostic, prognostic, and community frames prior to an election was associated with higher odds of a successful outcome. After elections, framing patterns diverged depending on results: after wins, the use of prognostic and motivational frames decreased, whereas after losses, the use of prognostic and engagement frames increased. By examining variation in message-level framing, the study highlights how communication strategies correlate with organizational success, contributing open tools and data, and complementing prior research in understanding digital communication of unions and social movements.
format Preprint
id arxiv_https___arxiv_org_abs_2510_01757
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Framing Unionization on Facebook: Communication around Representation Elections in the United States
Pera, Arianna
Jude, Veronica
Budak, Ceren
Aiello, Luca Maria
Computers and Society
Social and Information Networks
Physics and Society
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 social media 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. Greater use of diagnostic, prognostic, and community frames prior to an election was associated with higher odds of a successful outcome. After elections, framing patterns diverged depending on results: after wins, the use of prognostic and motivational frames decreased, whereas after losses, the use of prognostic and engagement frames increased. By examining variation in message-level framing, the study highlights how communication strategies correlate with organizational success, contributing open tools and data, and complementing prior research in understanding digital communication of unions and social movements.
title Framing Unionization on Facebook: Communication around Representation Elections in the United States
topic Computers and Society
Social and Information Networks
Physics and Society
url https://arxiv.org/abs/2510.01757