Tweet's popularity dynamics
This is an incremental study on understanding tweet popularity dynamics for social media analysis, with no significant results reported.
The project attempted to automatically identify patterns in tweet popularity evolution using machine learning and deep learning, but the algorithm ultimately failed to automate the task, highlighting the complexity of virality on social networks.
This article charts the work of a 4 month project aimed at automatically identifying patterns of tweets popularity evolution using Machine Learning and Deep Learning techniques. To apprehend both the data and the extent of the problem, a straightforward clustering algorithm based on a point to point distance is used. Then, in an attempt to refine the algorithm, various analyses especially using feature extraction techniques are conducted. Although the algorithm eventually fails to automate such a task, this exercise raises a complex but necessary issue touching on the impact of virality on social networks.