Instagram users’ meaning construction through micro-influencer-generated content
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Notice bibliographique
Résumé
In 2019, Instagram is the fastest-growing social platform with over a billion monthly users sharing more than 95 million images and videos daily. Social media influencers have become a new, effective way of reaching the right target audience and building relationships between brands and consumers. \n \nThe purpose of this study is to understand how meanings are constructed by the followers of Instagram micro-influencers. Furthermore, this study exposes the factors that explain micro-influencer following. \n \nThe theoretical framework consists of the uses and gratifications theory, meaning construction, semiotics and influence theories. Based on these theories, the theoretical framework focuses on an individual’s meaning construction, which is influenced by memories, values, culture, language, beliefs, motivations, social relations and media usage. The meanings in an image are a negotiation between the producer and the viewer, and reflect individual values, attitudes and political, social and cultural beliefs. Meanings are therefore produced between the micro-influencers’ content and the interpretation of the follower. \n \nThe research questions were answered through insight provided by ten in-depth ZMET interviews that were conducted in Finland and in Canada. Four emerging thematic meaning constructs and factors, four core meanings and multiple subthemes were found that explain Instagram’s micro-influencer following and relationship formation. \n \nIt was found that a sense of similarity, shared meanings and personality presented through visual content by the micro-influencer has a substantial impact on micro-influencer following. In addition, the results confirmed that people seek motivation, inspiration and confirmation of their own beliefs, situations and experiences in life from the micro-influencer and build a sense of belonginess and themselves. Based on the results of this research, a model of the different levels of relationship formation was created. The study gives insight into the various aspects of influencer marketing that need to be taken into consideration by practitioners and gives guidance on how to create compelling influencer marketing strategies and campaigns through meaningful content in order to form valuable relationships with consumers.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,002 |
| Communication savante | 0,000 | 0,002 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,002 | 0,001 |
| 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 découle