Public Response on Social Media to a Social Marketing Campaign for Influencing Attitudes towards Boating Safety
Notice bibliographique
Résumé
The purpose of this research paper is to assess the response on Facebook to a social marketing campaign for recreational boating safety. The campaign ran for the 2018 and 2019 boating seasons in British Columbia, Canada. Messages related to boating safety were delivered in multi-media formats, including ten Facebook posts. All public comments on the campaign Facebook page in response to the ads were included in the analysis. Comments were reviewed for tone and subject; those that related directly to the campaign or boating safety-related topics, such as alcohol use or enforcement, were labeled positive, negative or neutral in tone. Metrics such as likes and shares were also noted. The overall engagement rate (defined as engagements over people reached) was 4.1%. The posts were liked >7000 times and received 901 shares. A total of 219 comments were analysed. Almost half of the comments were positive (n = 106, 48.4%). Fifty comments were off-topic (22.8%), 45 were neutral (20.5%) and 18 were negative (8.2%). The majority of comments were positive, indicating that the campaign performed as planned and was generally well received by the people for whom it was intended. Comments illuminated prevailing attitudes towards risks, injuries and safety practices related to recreational boating. Positive comments valued safety as an aspect of having a pleasant experience, rather than a barrier. Negative comments were about perceiving reduced fun of boating, rather than objecting to the campaign itself. As a component of a multi-media social marketing strategy, Facebook can be a source of instant feedback from the campaign audience.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».