Social bots shape public issue networks in China’s dual-carbon agenda: a network analysis using MRQAP

Abstract

Abstract Despite growing recognition of social bots’ role in swaying public opinion, evidence of their specific impact on public cognition remains limited. Applying the network agenda-setting theory and multiple regression quadratic assignment procedure (MRQAP) analysis of X (formerly Twitter) posts, we examine the relative impact of social bots and legacy media on public agenda networks over time, focusing on China’s dual-carbon policy. Findings reveal that social bots’ agenda networks exert a significant influence on public agenda networks, with their impact being more pronounced than that of legacy media during the initial period (T1). However, this influence diminishes in the subsequent period (T2), suggesting that social bots have a potent yet short-lived effect on shaping public cognitive networks around specific issues. Furthermore, social bots exhibited more negative attitudes towards dual-carbon topics, contrasting with the neutral stance of legacy media. A comparative semantic network analysis highlights the distinct narrative structures promoted by social bots and legacy media. This research provides crucial insights into automated actors’ roles in molding environmental discourse and public perception.