A carregar...
Publicação
Análise de sentimento de anúncios de storytelling de marcas de telecomunicações: Nos e Vodafone
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 2.25 MB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
O storytelling e a análise de sentimentos têm vindo a ganhar uma maior relevância, uma vez que a tecnologia nos permite partilhar histórias com o mundo e posteriormente avaliar o impacto emocional gerado. Com o crescimento das redes sociais, observa-se um aumento significativo nos comentários online, que por sua vez influenciam perceções e decisões de compra. No entanto, para garantir que existe eficácia na comunicação, é bastante importante que se analise estas interações e se compreenda os sentimentos expressos. O storytelling, quando aplicado como ferramenta estratégica, destaca-se pela capacidade de despertar emoções e de criar vínculos genuínos. Através desta abordagem, é possível estabelecer uma comunicação mais autêntica e emocionalmente envolvente assumindo a análise de sentimentos, neste contexto, um papel essencial, pois permite validar se as mensagens transmitidas correspondem efetivamente às reações desejadas. Para além disso, permite identificar as polaridades emocionais e apoiar a realização de reformulações estratégicas que melhorem a eficácia comunicacional. A presente dissertação tem como objetivo principal analisar os sentimentos expressos nos comentários de utilizadores do YouTube relativamente às campanhas de storytelling das marcas NOS e Vodafone. A investigação incide sobre as campanhas publicadas nos anos de 2023 e 2024, selecionadas por refletirem as estratégias mais recentes de comunicação emocional no setor das telecomunicações em Portugal. A recolha de dados foi realizada com o apoio da ferramenta YouTube Comments Downloader, que permitiu extrair automaticamente os comentários públicos associados aos vídeos analisados. Após a recolha, os dados foram revistos manualmente para garantir a autenticidade e a relevância das interações incluídas. Posteriormente, os comentários foram processados na aplicação RapidMiner, recorrendo a técnicas de text mining e algoritmos de machine learning para classificar as expressões segundo a sua polaridade emocional. Os resultados obtidos permitiram comparar a eficácia emocional das campanhas das duas marcas, destacando diferenças significativas na forma como as narrativas foram percecionadas pelos consumidores. A análise revelou ainda padrões distintos de envolvimento afetivo e de reação emocional, proporcionando insights relevantes para compreender como os públicos respondem às estratégias de storytelling atualmente utilizadas no setor das telecomunicações
Storytelling and sentiment analysis have been gaining increasing relevance, as technology now allows us to share stories with the world and subsequently evaluate the emotional impact they generate. With the growth of social media, there has been a significant rise in online comments, which in turn influence perceptions and purchasing decisions. However, to ensure communication effectiveness, it is essential to examine these interactions and understand the feelings expressed within them. When used as a strategic tool, storytelling stands out for its ability to evoke emotions and create genuine connections. Through this approach, it becomes possible to establish more authentic and emotionally engaging communication. In this context, sentiment analysis plays a crucial role, as it allows us to assess whether the messages conveyed effectively align with the intended audience reactions. Moreover, it enables the identification of emotional polarities and supports strategic refinements that enhance communicational effectiveness. The main objective of this dissertation is to examine the feelings expressed in YouTube user comments regarding the storytelling campaigns of the brands NOS and Vodafone. The research focuses on campaigns published in 2023 and 2024, selected for representing the most recent emotional communication strategies within the Portuguese telecommunications sector. Data collection was carried out using the YouTube Comments Downloader tool, which enabled the automatic extraction of public comments associated with the selected videos. After extraction, the comments were manually reviewed to ensure the authenticity and relevance of the interactions. Subsequently, the dataset was processed in RapidMiner using text mining techniques and machine learning algorithms to classify expressions according to their emotional polarity. The results obtained allowed for a comparison of the emotional effectiveness of both brands’ campaigns, highlighting significant differences in how the narratives were perceived by consumers. The analysis also revealed distinct patterns of affective engagement and emotional response, providing valuable insights into how audiences react to contemporary storytelling strategies within the telecommunications industry.
Storytelling and sentiment analysis have been gaining increasing relevance, as technology now allows us to share stories with the world and subsequently evaluate the emotional impact they generate. With the growth of social media, there has been a significant rise in online comments, which in turn influence perceptions and purchasing decisions. However, to ensure communication effectiveness, it is essential to examine these interactions and understand the feelings expressed within them. When used as a strategic tool, storytelling stands out for its ability to evoke emotions and create genuine connections. Through this approach, it becomes possible to establish more authentic and emotionally engaging communication. In this context, sentiment analysis plays a crucial role, as it allows us to assess whether the messages conveyed effectively align with the intended audience reactions. Moreover, it enables the identification of emotional polarities and supports strategic refinements that enhance communicational effectiveness. The main objective of this dissertation is to examine the feelings expressed in YouTube user comments regarding the storytelling campaigns of the brands NOS and Vodafone. The research focuses on campaigns published in 2023 and 2024, selected for representing the most recent emotional communication strategies within the Portuguese telecommunications sector. Data collection was carried out using the YouTube Comments Downloader tool, which enabled the automatic extraction of public comments associated with the selected videos. After extraction, the comments were manually reviewed to ensure the authenticity and relevance of the interactions. Subsequently, the dataset was processed in RapidMiner using text mining techniques and machine learning algorithms to classify expressions according to their emotional polarity. The results obtained allowed for a comparison of the emotional effectiveness of both brands’ campaigns, highlighting significant differences in how the narratives were perceived by consumers. The analysis also revealed distinct patterns of affective engagement and emotional response, providing valuable insights into how audiences react to contemporary storytelling strategies within the telecommunications industry.
Descrição
Palavras-chave
Storytelling Análise de Sentimento Redes Sociais Comentários Online Sentiment Analysis Social Media Online Comments