no code implementations • 19 Jun 2015 • Emilio Ferrara, Zeyao Yang
This work aims at quantifying the effect of sentiment on information diffusion, to understand: (i) whether positive conversations spread faster and/or broader than negative ones (or vice-versa); (ii) what kind of emotions are more typical of popular conversations on social media; and, (iii) what type of sentiment is expressed in conversations characterized by different temporal dynamics.
no code implementations • 19 Jun 2015 • Emilio Ferrara, Zeyao Yang
We highlight the presence of a linear relationship between the average emotional valence of the stimuli users are exposed to, and that of the responses they produce.
