Impact of ByteDance crisis communication strategies on different social media users

Abstract

The impact of corporate crisis communication strategies on users’ attitudes across different platforms has emerged as a new focal point in crisis management. This study is rooted in Social Media Crisis Communication (SMCC) and employs the case of Trump’s sanctions on TikTok to analyze variations in the effects of ByteDance’s crisis communication strategies on different social media platforms. We initally identified five announcements that generated significant discussions on Toutiao and Weibo and collected the corresponding user comments (a total of 50,702). Subsequently, we utilized two approaches, machine learning and deep learning, to conduct sentiment classification tests on the text to identify the best-performing model. This model was then applied on the entire dataset for sentiment classification, followed by semantic network analysis based on the sentiment classification results. The results demostrated that the pre-trained ERNIE model outperformed the other tested models (F1 = 82.40%). Following the fourth crisis communication event, users on Toutiao and Weibo exhibited contrasting sentimental tendencies. Theoretically, we observed that users on different social media platforms relying on distinct information sources, expressed different sentimental responses to the same crisis. Social media users have a tendency to anthropomorphize corporate personality traits. In practical terms, we recommend that companies engage in crisis communication on multiple social media platforms and do not overlook the most influential platforms in the market.