An Empirical Study of User Engagement in Influencer Marketing on Weibo and WeChat

Understanding social media users’ engagement is one of the most crucial steps in a successful deployment of an influencer marketing campaign. On mainstream social media platforms, opinion leaders are the major channels to spread opinions and media content to a large population of consumers. Therefore, analyzing how users respond to the blogs of opinion leaders lies at the core of understanding user engagement in social media. In this article, to study the factors that have great impacts on user engagement, we first collect a cross-platform opinion leaders’ blogs dataset, which includes 344 643 blogs published by 93 opinion leaders who have accounts on both Weibo and WeChat, the two most popular social media platforms in China. Based on this dataset, we conduct both characteristics study and semantic study to investigate the impact factors of user engagement with respect to blogs of opinion leaders. To find out the associations between user engagement and practically accessible attributes of opinion leaders and their blogs, we adopt state-of-the-art (SOTA) sentiment analysis models to process the blog data, develop a normalization technique to alleviate the issue caused by the heterogeneity of fall-out intervals of blogs, and devise a saliency method to compute the integrated gradients of sentences in blogs. Utilizing these computational tools, we reveal that user engagement on the two platforms agrees on some common factors, such as the number of tokens of blogs. Meanwhile, the two platforms differ in some aspects. For example, the semantic patterns that can improve the level of user engagement on the two platforms are very different. Our analysis can provide advertisers with valuable insights on how to plan an influencer marketing campaign on the two platforms.