{"title":"The impact of executives’ social media disclosure on pricing efficiency of the capital market","authors":"Mingchuan Zhong, Xin Chen, Kedi Wang, Yanzhen Yao","doi":"10.1016/j.procs.2026.08.053","DOIUrl":null,"url":null,"abstract":"<div><div>With the rapid expansion of the digital economy, social media platforms like Weibo have become crucial frontiers for interaction between corporate executives and investors. This study investigates Shanghai and Shenzhen A-share listed companies from 2010 to 2025. By utilizing Python-based web-crawling techniques to collect post data from verified personal executive accounts, this paper empirically examines the impact of executive social media disclosure on capital market pricing efficiency. The results indicate that executives’ social media presence significantly reduces stock price synchronicity, thereby enhancing capital market pricing efficiency. This finding supports the information effect hypothesis, suggesting that executives disclose firm-specific information through social media, which effectively mitigates information asymmetry between firms and investors. Consequently, stock prices are enabled to more accurately reflect the intrinsic and independent value of the enterprise. Endogeneity tests further confirm the robustness of these conclusions after controlling for reverse causality. These findings not only enrich the literature on executive behavior and asset pricing but also offer references for regulatory authorities to standardize disclosure norms in the new media era and provide practical insights for investors leveraging unstructured data for decision-making.</div></div>","PeriodicalId":20465,"journal":{"name":"Procedia Computer Science","volume":"287 ","pages":"Pages 311-318"},"PeriodicalIF":0.0000,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Procedia Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1877050926026888","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/9/18 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With the rapid expansion of the digital economy, social media platforms like Weibo have become crucial frontiers for interaction between corporate executives and investors. This study investigates Shanghai and Shenzhen A-share listed companies from 2010 to 2025. By utilizing Python-based web-crawling techniques to collect post data from verified personal executive accounts, this paper empirically examines the impact of executive social media disclosure on capital market pricing efficiency. The results indicate that executives’ social media presence significantly reduces stock price synchronicity, thereby enhancing capital market pricing efficiency. This finding supports the information effect hypothesis, suggesting that executives disclose firm-specific information through social media, which effectively mitigates information asymmetry between firms and investors. Consequently, stock prices are enabled to more accurately reflect the intrinsic and independent value of the enterprise. Endogeneity tests further confirm the robustness of these conclusions after controlling for reverse causality. These findings not only enrich the literature on executive behavior and asset pricing but also offer references for regulatory authorities to standardize disclosure norms in the new media era and provide practical insights for investors leveraging unstructured data for decision-making.