Panorama do mercado no Social CRM: uma análise dos anúncios de emprego
Resumo
Com o surgimento das mídias sociais, o CRM tradicional evoluiu para o Social CRM, integrando a nova forma de interação para a gerenciamento do relacionamento com o cliente. Dessa forma, surge a necessidade de acompanhar o ritmo de mercado e identificar os elementos-chave para ingressar nessa área. O objetivo desse trabalho consiste em aplicar as técnicas de mineração de texto nas vagas de emprego online relacionadas ao Social CRM, com foco na identificação dos domínios do conhecimento e o conjunto de habilidades necessárias. A análise forneceu um conjunto de competências tecnológicas e os conhecimentos necessários. Nesse sentido, esse trabalho auxilia os candidatos e empregadores a identificarem as principais necessidades do setor.Referências
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Malthouse, E. C., Haenlein, M., Skiera, B., Wege, E., and Zhang, M. (2013). Managing customer relationships in the social media era: Introducing the social crm house. Journal of interactive marketing, 27(4):270–280.
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Boselli, R., Cesarini, M., Marrara, S., Mercorio, F., Mezzanzanica, M., Pasi, G., and Viviani, M. (2018). Wolmis: A labor market intelligence system for classifying web job vacancies. Journal of intelligent information systems, 51:477–502.
Charmaz, K. and Thornberg, R. (2021). The pursuit of quality in grounded theory. Qualitative research in psychology, 18(3):305–327.
Cirqueira, D., Pinheiro, M. F., Jacob, A., Lobato, F., and Santana, Á. (2018). A literature review in preprocessing for sentiment analysis for brazilian portuguese social media. In IEEE/WIC/ACM International Conference on Web Intelligence (WI). IEEE.
Costa, G. d. S., Couto, D. C., Junior, A. F. J., and Lobato, F. M. (2022). Feminismo e redes sociais online: uma análise de tweets sobre o dia internacional da mulher. In Anais do XI Brazilian Workshop on Social Network Analysis and Mining, pages 169–180. SBC.
Ghazzawi, K. and Accoumeh, A. (2014). Critical success factors of the e-recruitment system. Journal of Human Resources Management and Labor Studies, 2(2):159–170.
Grootendorst, M. (2022). Bertopic: Neural topic modeling with a class-based tf-idf procedure. arXiv preprint arXiv:2203.05794.
Kureková, L. M., Beblavỳ, M., and Thum-Thysen, A. (2015). Using online vacancies and web surveys to analyse the labour market: A methodological inquiry. IZA Journal of Labor Economics, 4:1–20.
Lobato, F. M., Silva Junior, J. L., Jacob, A., and Lisboa Cardoso, D. (2020). Social crm: A literature review based on keywords network analysis. In Business Information Systems Workshops: BIS 2020 International Workshops, Colorado Springs, CO, USA, June 8–10, 2020, Revised Selected Papers 23, pages 237–249. Springer.
Malthouse, E. C., Haenlein, M., Skiera, B., Wege, E., and Zhang, M. (2013). Managing customer relationships in the social media era: Introducing the social crm house. Journal of interactive marketing, 27(4):270–280.
Wirth, R. and Hipp, J. (2000). Crisp-dm: Towards a standard process model for data mining. In Proceedings of the 4th international conference on the practical applications of knowledge discovery and data mining, volume 1, pages 29–39. Manchester.
Publicado
30/10/2023
Como Citar
MENEZES, Pedro C.; JUSTINO, Adrielson F.; BARATA, Barbara A. P.; SILVA, Marcelino S. da; JACOB JUNIOR, Antonio F. L.; LOBATO, Fábio M. F..
Panorama do mercado no Social CRM: uma análise dos anúncios de emprego. In: ESCOLA REGIONAL DE ALTO DESEMPENHO NORTE 2 (ERAD-NO2) E ESCOLA REGIONAL DE APRENDIZADO DE MÁQUINA E INTELIGÊNCIA ARTIFICIAL NORTE 2 (ERAMIA-NO2), 3. , 2023, Belém/PA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
.
p. 13-16.
DOI: https://doi.org/10.5753/erad-no2.2023.236281.
