One of the most important points in the design and implementation of any research is choosing the appropriate method that fits the topic and goals of the research and the ability to implement that method. Now, is it possible to compare human units and social realities (societies, literary and human products, artistic styles, moral and legal rules, etc. )? The problem of the current research is in what cases and how the comparative method can be used and what is the status of the research conducted with the comparative methodology in the field of social studies in Iran.? Methodology: The current research is a descriptive-analytical research, which according to its purpose is part of applied research, and according to the nature of its data, it is in the category of quantitative research, and according to the method of data collection, it is part of documentary methods. take The statistical population of this research is all journals with the label "scientific-research" (5161 scientific articles). The findings of the research show that the most researches based on comparative methodology are related to: 1. "Literature and Languages", 2. "Law", 3. "Religious Sciences", 4. "Art" ", 5. "Social studeis, and it is.

Purpose: Managers are one of the important elements of an organization, for this reason, in order to draw the future of the organization, it is necessary for the planners to specify the conditions of their selection and appointment. Therefore, the current research has been done with the aim of identifying and analyzing the components of selecting future principals.Method: In this research, comparative and benchmarking method is used as a prospective approach. This approach is based on the belief that today's advanced organizations/countries can be considered as a model for the future of another organization/countries in their respective subjects. For this, first, the fields of comparison and benchmarking were determined using Brody's four-step comparison method; then the countries of Canada, Finland, Australia, South Africa, and Japan were selected according to the qualitative balance value in the international advanced TEAMS test, human development index, life quality index(health, instruction, and welfare), education quality index, and other scientific-scholarly indexes; finally, by extracting the criteria for the selection and appointment of principals through content analysis and comparison with Iran, the proposed framework for Iran has been presented.Findings: A total of 61 components for the selection of secondary school principals were identified from among the studies conducted in the selected countries in this article. By extracting the commonalities and differences of each of the components among the countries, it was found that the highest index of manager selection and appointment belongs to Japan and the lowest one is related to Finland.Conclusion: There are similarities between the components of selection of principals of secondary schools in Iran and selected countries. In Iran, special attention should be paid to important components such as adherence to religious principles, appropriate personality traits, creativity and innovation, motivation to develop capabilities, professional growth, power of supervision and accountability, social image, leader skills, and purposefulness and foresight.

Automatic topic detection seems unavoidable in social media analysis due to big text data which their users generate. Clustering-based methods are one of the most important and up-to-date categories in topic detection. The goal of this research is to have a wide study on this category. Therefore, this paper aims to study the main components of clustering-based-topic-detection, which are embedding methods, distance metrics, and clustering algorithms. Transfer learning and consequently pretrained language models and word embeddings have been considered in recent years. Regarding the importance of embedding methods, the efficiency of five new embedding methods, from earlier to recent ones, are compared in this paper. To conduct our study, two commonly used distance metrics, in addition to five important clustering algorithms in the field of topic detection, are implemented by the authors. As COVID-19 has turned into a hot trending topic on social networks in recent years, a dataset including one-month tweets collected with COVID-19-related hashtags is used for this study. More than 7500 experiments are performed to determine tunable parameters. Then all combinations of embedding methods, distance metrics and clustering algorithms (50 combinations) are evaluated using Silhouette metric. Results show that T5 strongly outperforms other embedding methods, cosine distance is weakly better than other distance metrics, and DBSCAN is superior to other clustering algorithms.