Proposal of INDIRECT X Mentions as an Altmetrics Indicator: Dissemination of Research Papers on X via Web News and Blogs

This study reexamines the potential of altmetrics as indicators for evaluating the societal impact of research, focusing specifically on X (formerly Twitter). Existing X-based metrics primarily measure first-order citations —posts that directly link to academic papers. However, such metrics overlook second-order citations , which disseminate research indirectly through intermediary webpages such as news articles and blogs. To address this gap, we propose a new indicator, INDIRECT X mentions, designed to quantify the indirect dissemination of scholarly outputs. Using data from the artificial intelligence (AI) domain, this study compares the performance of DIRECT and INDIRECT X mentions over a 1.5-year period following publication. The results reveal that second-order citations occur at a comparable scale to first-order citations and exhibit distinctive diffusion characteristics: while INDIRECT X mentions demonstrate lower immediacy, they sustain engagement over a longer period. Furthermore, network analysis shows that the two metrics are generated by largely non-overlapping user groups, with INDIRECT X mentions associated more strongly with non-academic and media users. These findings suggest that INDIRECT X mentions provide a complementary perspective for measuring how academic knowledge circulates and resonates beyond scholarly communities, offering a more comprehensive framework for assessing the societal reach of research.