An Analysis on User Searches Effects
Nunziato Cassavia, Elio Masciari, Chiara Pulice, Domenico Saccà · 2018
Big Data new paradigm forced both researchers and industries to rethink data management techniques which became inadequate in many context. Indeed, we deal everyday with huge amounts of collected data about user suggestions and searches. These data requires new advanced analysis strategies to be devised in order to profitably leverage these information. Moreover, due to the heterogeneous and fast changing nature of these data, we need to adopt leverage new data storage and management tools to effectively store them. In this paper, we analyze the effect of user searches and suggestions and we try to understand how much they influence users social environment. This task is crucial to perform efficient identification of those users able to spread their influence across the network. Gathering information about user preferences is a key activity in several scenarios like tourism promotion, personalized marketing marketing, and entertainment suggestion. We show the application of our approach for a huge research project named D-ALL that stands for Data Alliance.