Bibliometric behavior of big data and digital marketing as real-time multimedia

Technological trends such as big data have generated interest in its application in digital marketing, due to the ease of precision in business and in daily decision-making, where there is a need to respond to the needs of the market in real time and achieve competitiveness. We aim to describe the bibliometric behavior of big data and digital marketing as real-time multimedia applications during the period from 2012 to 2023. We based our methodology on the bibliometric analysis of statistical relationships using VOSviewer software. We employed the normalization technique and applied the association strength method for keyword co-occurrence analysis and author co-citation analysis. Additionally, we used the hermeneutic technique to interpret the results. The findings indicate that research trends are associated with social networks; data processing; machine learning techniques; real-time system; online system; data analysis; data management. The contributing authors were Wang Y.; Chen Y.; Liu Y.; Zhang X.; Wang X.; Wang J.; Zhang Y.; Li J. We concluded that the common software in the study includes Hadoop, Reduced Map, Apache Spark, Twitter, Apache Storm, Spark Transmission, Transformer, and Weibo.

• Autores: Ramírez Molina, Reynier Israel; Santamaria Ruiz, Mauricio junior; Monsalve Castro, Lady Carolina; Lay Raby, Nelson David; Hinojoza Montañez, Sebastian; García Samper, Martha
• Tipo de recurso: Documento de conferencia en no proceso
• Fecha de publicación: 2024
• Institución: Corporación Universidad de la Costa
• Repositorio: REDICUC - Repositorio CUC
• Idioma: eng
• OAI Identifier: oai:repositorio.cuc.edu.co:11323/14201
• Acceso en línea: https://hdl.handle.net/11323/14201; https://repositorio.cuc.edu.co/
• Palabra clave: Marketing digital; Big data; Artificial intelligence; Scientometric
• Rights: openAccess
• License: Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)