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Título : Identifying Twitter Users Influence and Open Mindedness Using Anomaly Detection
Autor : Prado Romero, Mario Alfonso
Fernández Oliva, Alberto
García Hernández, Lucina
Palabras clave : ANOMALY DETECTION;TWITTER;INFLUENCER SOCIAL NETWORKS
Fecha de publicación : 2018
Editorial : Springer
Citación : Prado-Romero M.A., Oliva A.F., Hernández L.G. (2018) Identifying Twitter Users Influence and Open Mindedness Using Anomaly Detection. In: Hernández Heredia Y., Milián Núñez V., Ruiz Shulcloper J. (eds) Progress in Artificial Intelligence and Pattern Recognition. IWAIPR 2018. Lecture Notes in Computer Science, vol 11047. Springer, Cham. https://doi.org/10.1007/978-3-030-01132-1_19
Resumen : Social networks help us to connect and share our thoughts with family and friends. Businesses want to take advantage of social media to better reach their customers, but traditional advertising results annoying for most social network users. As a result, the use of influencers to help a message reach their target audience has become a topic of great interest. Despite the many works in this field, detecting influence in social networks is still an open topic. In this work we propose to use anomaly detection for finding “influential” and “open minded” individuals in the Twitter network. Targeting these users can help advertisers to reach closed communities and to increase the spread of their message.
URI : https://repositorio.uci.cu/jspui/handle/123456789/9455
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