Ping, Qingyun (2025) Social media exposure and company carbon information disclosure: Evidence from Australia and Greater China. PhD thesis, Victoria University.

Abstract

This study examines whether media exposure is an influential factor in the amount and level of carbon information disclosure in corporate sustainability reporting. In the past decade there has been a growing debate about climate change and global warming, and carbon neutrality has become a key solution to environmental problems. Mounting carbon neutrality issues have led to an increasing amount of social media coverage. As popularity of social media grows exponentially, and more and more people are getting news through social media platforms, social media engenders an agenda-setting effect through the social sharing of environmental news (Meng, Chung & Zhang, 2023). This study examines how firm-level social media exposure influences corporate carbon information disclosure (CID) across Australia and Greater China (Mainland China, Hong Kong and Taiwan) from 2018 to 2023. Drawing on agendasetting and legitimacy theories, the research distinguishes between media volume and media sentiment and evaluates their differential impacts on the quantity and quality of disclosure. A sample of 400 listed firms is constructed, comprising the top 200 firms in Australia and the top 200 firms in Greater China by market capitalisation, yielding an unbalanced panel of firm-year observations over six years. Social media data are collected from Twitter (Australia, Hong Kong and Taiwan) and Weibo (Mainland China) using keyword-based retrieval of carbon-related posts. Media volume is measured as the firm-year count of carbon-related posts specific to each listed company, capturing the salience of each firm's own carbon practices in social media discourse. Media sentiment is quantified using the Janis–Fadner coefficient to capture directional tone. Corporate carbon disclosure is manually coded from annual and sustainability reports into multidimensional indices capturing disclosure quantity and quality. Firm-level controls include size, profitability (ROA), ownership structure and institutional proxies. Methodologically, the study integrates panel regressions with two-way firm and year fixed effects, contemporaneous and lagged specifications to test temporal dynamics, interaction models to examine platform and institutional moderation, and event-based regressions exploiting major climate policy shocks. The dual-temporal specification distinguishes between immediate market-driven responses and delayed policy-cycle responses, serving as a replicable diagnostic for identifying institutional channel type. Results show that the media-disclosure relationship is systematically conditioned by institutional context. Social media salience drives within-firm disclosure improvements in Australia through a market-driven investor-relations channel and in Mainland China through a state-policy compliance channel with a lagged temporal structure. Hong Kong and Taiwan show null salience effects attributable to regulatory ceiling effects. Media sentiment does not operate independently but requires a minimum salience threshold to activate the legitimacy repair mechanism, a condition met by most Weibo firms but rarely by Twitter firms. Platform architecture shapes the content-type rather than the magnitude of disclosure responses: Weibo disproportionately amplifies qualitative governance depth, while both platforms produce equivalent effects on disclosure volume. Climate policy events generate substantial next-year disclosure premiums on both platforms. The study contributes by: (i) developing a dual-pathway legitimacy model applicable across state-capitalist and market-capitalist contexts; (ii) demonstrating temporal asymmetry as a replicable institutional diagnostic; (iii) identifying structural preconditions for evaluative legitimacy repair; (iv) establishing a dual-signal threshold mechanism linking media volume and sentiment; and (v) showing that platform architecture shapes disclosure content-type rather than magnitude. The results offer policy-relevant insights for regulators and standard-setters seeking to leverage digital information environments to enhance climate transparency.

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