درخت حوزه‌های تخصصی

how crises are represented in elementary and high school textbooks through content analysis method. In the first step, the basic concepts related to this topic, were extracted from Iranian and international scientific and legal documents deductively. Then, 68 extracted concepts were put into 12 categories and were sent to the field experts in the form of a questionnaire.The reliability coefficient of the questionnaire was computed.88 with Cronbach's Alpha. The extracted categorieswere again offered to some field experts and validated. Based on confirmed categories, the content of textbooks (28 titles) and teacher's guidebooks (12 titles) were analyzed. The results of analyzing the textbooks show that the main focus is first on the issue of crisisology and the consequences of crises, and second, on preventive actions which encompass%80 of the content. The remainder of the related content was concerned with other topics; the contribution of the content that focused on resiliency and recovery is less than other concepts.The comparison of the weights allocated by the experts and the weights gained from the textbooks analysis was made by Mann-Whitney U and Chi square tests; in both tests, a meaningful difference was observed.

The impact of personal judgment on the assessment of an individual’s financial situation has been drastically reduced through the development of credit scoring. The systems are capable of deciding based on an applicant’s total score which is a combination of several factors and indicators. Over the past few decades, credit scoring has been considered an essential tool for evaluation in various institutions and has also been able to transform the industry as a whole. Most of the research conducted in the field has taken into account traditional credit scoring, but considering the ever-evolving technological world that we live in and the increasing emergence of new social media networks, such research has now become obsolete. Such technological advancements have not only paved the way for far more sophisticated credit scoring systems but also essentially rendered the previous generations useless. It should be noted that credit scoring and its features have widely been discussed across the globe but, considering the various aspects and models that have to be taken into account, no one best method has been designed or suggested for it so far. This study shows that social media channels tend to perform relatively well in predicting stock market trends when the overall index is growing positively. The research also illustrates that a higher number of days of activity and a large number of signals released do not necessarily mean that the channels can or have credited their offered stock return on a one-month time frame. The methodology used is "CRISP-DM," which consists of six steps. The main variables include social and financial variables that are examined for six months. In the research, we seek to identify, analyze and categorize active telegram channels in stock signals using the data mining model and the RFM method. The k-means algorithm is selected for this category. Then, in each cluster, the importance of social variables and the performance of the channels are extracted by the EXTRATREECLASSIFIER algorithm, and channel performance is measured by considering the changes in the total index.