  Opinions are influenced by neighbors, with varying degrees of emphasis based
on their connections. Some may value more connected neighbors' views due to
authority respect, while others might lean towards grassroots perspectives. The
emergence of ChatGPT could signify a new ``opinion leader'' whose views people
put a lot of weight on. This study introduces a degree-weighted DeGroot
learning model to examine the effects of such belief updates on learning
outcomes, especially the speed of belief convergence. We find that greater
respect for authority doesn't guarantee faster convergence. The influence of
authority respect is non-monotonic. The convergence speed, influenced by
increased authority-respect or grassroots dissent, hinges on the unity of elite
and grassroots factions. This research sheds light on the growing skepticism
towards public figures and the ensuing dissonance in public debate.
