Abstract Online health communities (OHCs) function as significant platforms that people use to obtain information and emotional support. Despite many studies on user behavior and relationships, little attention has been paid to user identities and how different layers of identities are interwoven. To address this potential research gap, this study examined users' relationship‐layer identities and their evolution by elaborating on the communication theory of identity (CTI) and social support theory. Additionally, based on our previous study on users' personal‐layer identities in OHCs, we investigated how users' relationship‐layer identities interacted with their personal‐layer identities. This study classified users' posts and replies into providing informational support, seeking informational support, providing emotional support, seeking emotional support, and companionship using the bidirectional encoder representation from transformers (BERT), with F1‐scores above 0.848. Through social network analysis, this study found that users of OHCs constructed their relationship‐layer identities more through informational interactions than through emotional interactions. Users with various personal‐layer identities presented different relationship‐layer identities. Users' relationships were more initiated by information exchange, and users with more interactions had more companionship activities. OHCs provided efficient communication channels for people to exchange social support.

Abstract Scientific papers are essential manifestations of evolving scientific knowledge, and arguments are an important avenue to communicate research results. This study aims to understand how the argumentation process is represented in scientific papers, which is important for knowledge representation, discovery, and retrieval. First, based on fundamental argument theory and scientific discourse ontologies, a coding schema, including 17 categories was constructed. Thereafter, annotation experiments were conducted with 40 scientific articles randomly selected from two different research areas (library and information science and biomedical sciences). Statistical analysis and the sequential pattern mining method were then employed; the ratio of different argumentation units and evidence types were calculated, the argumentation semantics of figures and tables analyzed, and the argumentation structures extracted. A correlation analysis between argumentation and rhetorical structures was also performed to further reveal how argumentation was represented within scientific discourses. The results indicated a difference in the proportion of the argumentation units in the two types of scientific papers, as well as a similar linear construction with differences in the specific argument structures of each knowledge domain and a clear correlation between argumentation and rhetorical structure.