
In today's era of widespread social media, predicting content popularity has become a hot topic. Social media is important because it affects the speed and scope of information dissemination. However, predictive models face challenges related to data sparsity, complex feature selection, model interpretability, real-time requirements, and computational resources. Optimization strategies are proposed, including enhancing data preprocessing, applying deep learning and transfer learning, introducing explainable AI technologies, and optimizing algorithms and resource utilization, with the aim of improving the accuracy and efficiency of predictive models.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
