Examining Hashtag Use of #blackboyjoy and #theblackmancan and Related Content on Instagram: Descriptive Content Analysis
Notice bibliographique
Résumé
BACKGROUND: Social media is widely accessible and increasingly utilized. Social media users develop hashtags and visual, text-based imagery to challenge misrepresentations, garner social support, and discuss a variety of mental health issues. Understanding how Black men are represented on social media and are using social media may be an avenue for promoting their engagement with and uptake of digital mental health interventions. OBJECTIVE: The aim of this study was to conduct a content analysis of posts containing visual and text-based components related to representations of Black men's race, gender, and behaviors. METHODS: An exploratory, descriptive content analysis was conducted for 500 Instagram posts to examine characteristics, content, and public engagement of posts containing the hashtags #theblackmancan and #blackboyjoy. Posts were selected randomly and extracted from Instagram using a social network mining tool during Fall 2018 and Spring 2019. A codebook was developed, and all posts were analyzed by 2 independent coders. Analyses included frequency counts and descriptive analysis to determine content and characteristics of posts. Mann-Whitney U tests and Kruskal-Wallis H tests were conducted to assess engagement associated with posts via likes, comments, and video views. RESULTS: Of the 500 posts extracted, most were image based (368/500, 73.6%), 272/500 (54.4%) were posted by an individual and 135/500 (27.0%) by a community organization, 269/500 (53.8%) were posted by individuals from Black populations, and 177/500 (35.4%) posts contained images of only males. Posts depicted images of Black men as fathers (100/500, 20.0%), Black men being celebrated (101/500, 20.2%), and Black men expressing joy (217/500, 43.4%). Posts (127/500, 25.4%) also depicted Black men in relation to gender atypical behavior, such as caring for children or styling their children's hair. Variables related to education and restrictive affection did not show up often in posts. Engagement via likes (median 1671, P<.001), comments (P<.001), and views (P<.001) for posts containing #theblackmancan was significantly higher compared with posts containing #blackboyjoy (median 140). Posts containing elements of celebrating Black men (P=.02) and gender atypical behavior (P<.001) also had significantly higher engagement. CONCLUSIONS: This is one of the first studies to look at hashtag use of #blackboyjoy and #theblackmancan. Posts containing #blackboyjoy and #theblackmancan promoted positive user-generated visual and text-based content on Instagram and promoted positive interactions among Black and diverse communities. With the popularity of social media and hashtag use increasing, researchers and future interventional research should investigate the potential for such imagery to serve as culturally relevant design components for digital mental health prevention efforts geared towards Black men and the communities they exist and engage with.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,005 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».