Título:	Data analysis in social networks for agribusiness: a systematic review.
Autoria:	SOARES, N. D. BRAGA, R. DAVID, J. M. N. SIQUEIRA, K. B. STROELE, V.
Afiliação:	NEDSON D. SOARES, Energisa; REGINA BRAGA, Universidade Federal de Juiz de Fora; JOSÉ MARIA N. DAVID, Universidade Federal de Juiz de Fora; KENNYA BEATRIZ SIQUEIRA, CNPGL; VICTOR STROELE, Universidade Federal de Juiz de Fora.
Ano de publicação:	2023
Referência:	IEEE Access, v. 11, p. 8422-8432, 2023.
Conteúdo:	The ability of companies to react to changes imposed by the market can be aided by to information acquisition and knowledge generation. Big data technologies, crowdsourcing, and Online Social Networks (OSN) are used for knowledge generation. These technologies have assumed a significant position in agribusiness in recent decades. This work investigates how social network analysis can promote agribusiness to provide a basis for future applications and evaluations. We adopted a hybrid systematic mapping to conduct the investigation. Two hundred twenty-three works that propose solutions for agribusiness were found and categorized. Results showed the most used OSN is Twitter and revealed an increase in the number of studies in this area. The information obtained indicates how social media monitoring can complement traditional decision-making methods in managing and regulating agricultural systems. However, more studies in agribusiness using data analysis tools on social networks are required, considering the importance of social networks on marketing strategies. Based on our results, we discuss some challenges and research directions.
Thesagro:	Agronegócio Análise de Dados
Palavras-chave:	Mapeamento sistemático Rede social
Digital Object Identifier:	https://doi.org/10.1109/ACCESS.2023.3237984
Tipo do material:	Artigo de periódico
Acesso:	openAccess
Aparece nas coleções:	Artigo em periódico indexado (CNPGL)