چكيده لاتين
Scientific communication in the realm of humanities is a multidimensional variable with various aspects and numerous components, which require understanding for its study and comprehension. Therefore, the main objective of this research is to identify the components of scientific communication in texts using conceptual clustering methods to provide a comprehensive model suitable for the context of humanities and to represent this model from an ontological perspective. This study is applied in terms of purpose and follows a sequential mixed-methods explanatory approach, comprising four distinct phases where methods such as data mining, content analysis, Delphi method, and structural interpretive modeling were utilized. The statistical population of this research at different stages included articles related to the topic of scientific communication from the Scopus and Web of Science databases, as well as specialists and experts in the field of scientific communication in the humanities. The selection and identification of experts were conducted using a snowball sampling method through referrals from other experts. The criteria for selecting experts included theoretical mastery, practical experience, willingness, ability to participate in the research, and accessibility. Data collection tools included questionnaires and interviews, and for data analysis at various stages, different tools and software were employed, such as Excel for initial data organization, Python coding for text mining, SPSS for statistical analysis, and JavaScript coding for modeling from an ontological perspective. The findings from the first and second phases led to the extraction of terms and concepts that were categorized into nine general categories. The findings from the structural interpretive modeling phase resulted in a hierarchical arrangement, indicating that at the first level, financial and contextual factors; at the second level, information and communication technologies and human factors; at the third level, research infrastructure; at the fourth level, researcher skills and capabilities; at the fifth level, content exchanged and research interactions; and at the final level, evaluation factors were situated. Clustering in the Micmac diagram, based on the degree of influence and dependency, resulted in three clusters: financial factors, contextual factors, information and communication technologies, and research infrastructure in the first cluster (independent variable area); human factors in the second cluster (self-regulating variable area); and other components in the third cluster (dependent variable area). Additionally, financial and contextual factors, as independent variables with the greatest influence, serve as the foundation and main drivers for the formation and strengthening of the scientific communication system. These factors have the most significant impact on the field of scientific communication in the humanities, and changes in them will lead to transformations within the system. Research interactions, exchanged content, and evaluation are positioned at the final levels of this model, influenced by other factors but having minimal or no effect on other variables. Other results indicated that dependent variables possess low influence and high dependency, making them less likely to serve as precursors for other variables. Furthermore, in the model of scientific communication in the humanities from an ontological representation, nine main components were considered as entities, and 15 types of relationships among them were identified. These relationships included influence, reinforcement, funding, support, facilitation, production, evaluation, and others.
