The Python code used for scraping Sina Weibo.

Social media platforms provide the public with a forum for interaction and communication with tourism destinations, playing a significant role in the shaping and dissemination of destination images. Similarly, social media plays a vital role in the construction and propagation of online images for higher education institutions. For instance, indicators such as likes, shares, and visits on Weibo can serve as measures of public engagement with university social media. To reveal the triggering rules of social media engagement by projected images of destinations and related factors, this paper builds a Bayesian model using data from posts and interactions on the official Sina Weibo account of a Chinese university from 2018 to 2023. This model simulates to infer the optimal decisions that trigger university social media engagement.社交媒体平台为公众提供了与旅游目的地开展互动与交流的论坛，在目的地形象的塑造与传播中发挥着重要作用。同样，社交媒体在高等教育机构的线上形象构建与传播中也扮演着至关重要的角色。例如，微博（Weibo）平台上的点赞、转发与浏览量等指标，可作为衡量公众对高校社交媒体参与度的有效依据。为揭示目的地投射形象及其相关因素对社交媒体参与度的触发规律，本文基于2018年至2023年某中国高校官方新浪微博（Sina Weibo）账号的发帖与互动数据，构建了贝叶斯（Bayesian）模型。该模型通过模拟推演，可推断出能够触发高校社交媒体参与度的最优决策方案。