How Regional Stereotypes are Narrated in News Comments: An Analysis of TikTok Platform Based on LDA Model
Abstract
This study examines regional stereotypes in new media comment sections, focusing on TikTok. Using the Latent Dirichlet Allocation (LDA) model, researchers analyze comments to uncover how social cognitive biases contribute to these stereotypes.
The research finds that stereotypes often stem from collective social memories and spread rapidly on social media following news events, shaping public discourse. The study investigates the theft incident at the 2023 Midi Music Festival in Nanyang, Henan, using TikTok comment sections to identify narrative frameworks like objective reporting, irony, symbolism, and image reflection.
These frameworks reflect public attitudes and the evolution of regional stereotypes in digital spaces. The study suggests that socioeconomic status, media reporting, and regional identity influence stereotype propagation. It proposes promoting positive portrayals on social media to improve regional images.
This research informs strategies for fostering a harmonious online environment, advocating for technological enhancements in news platforms to diversify and positively represent geographic information dissemination.