مطالب

World of technology provides everyone with a great outlet to give their opinion, using social media like Twitter and other platforms. This paper employs machine learning methods for text analysis to obtain sentiments of reviews by the people on twitter. Sentiment analysis of the text uses Natural language processing, a machine learning technique to tell the orientation of opinion of a piece of text. This system extracts attributes from the piece of writing such as a) The polarity of text, whether the speaker is criticizing or appreciating, b) The topic of discussion, subject of the text. A comparison of the work done so far on sentiment analysis on tweets has been shown. A detailed discussion on feature extraction and feature representation is provided. Comparison of six classifiers: Naïve Bayes, Decision Tree, Logistic Regression, Support Vector Machine, XGBoost and Random Forest, based on their accuracy depending upon type of feature, is shown. Moreover, this paper also provides sentiment analysis of political views and public opinion on lockdown in India. Tweets with ‘#lockdown’ are analysed for their sentiment categorically and a schematic analysis is shown.

Corporate Social Responsibility (CSR) is a general concept where companies voluntarily decide to adopt social, economic and environmental responsibilities for a better society and environment. Researchers in the management field have created various CSR models and theories. Moreover, enterprises are working out to strength its competitiveness performance though adopting CSR approaches. For that, decision makers in an enterprise have to target the most appropriate CSR approach that fit with the environment and the nature of their enterprise. The Analytical Hierarchy Process (AHP) has been presented through the article in order to help an organization take decision toward the most convenient CSR method according to many characteristics and criteria.

Education is not limited to chalk and talk in the 21st century, but learning science is possible through different formats and methods. Meanwhile, visual representations of a city could be considered by a system of signs and based on the opposition between emotional motivation and the visible structure of the material world and through a complex system of signs, as well as social, economic, and cultural characteristics of the communities. Hence, these visual representations of the cities play an important role in the metamorphosis of urban spaces; besides reproduction or elimination and decline of semantic values during time. With this approach, the main purpose of this paper is to study the function feasibility of theme parks in the realization of learning city. This topic is important for urban planning studies, more than ever with respect to the concepts and theoretical and practical configurations. In regard to its purpose and nature, this study is an applied research, and based on its method it is a descriptive-analytical study. The study was carried out in September 2017. Thus, 34 items with seven components and four indicators have been identified to check the thematic parks for the realization of a learning city. Mental model software is used to analyze the performance of the indicators. Confirmatory factor analysis was used in SMART PLS software to confirm or reject the performance findings of the indicators. The research results showed that the items have been effective in the theme parks with different coefficients (from high to low impacts) and with an increasing trend in the realization of learning city, in this way, the indicators of continuity in activities, creating conditions for healthy competition, identifying competencies and moral excellence have had the greatest impacts and centrality with effect 11.21, 10.58, 10.45 and 10.41, respectively. Also, the findings of confirmatory factor analysis showed a strong relationship between the performance of theme parks and the learning city by confirming the relationship among the indicators, in Mellat Park of Zanjan.

The present study was conducted to determine the effectiveness of parenting skills training based on a solution-oriented approach to internalization disorders in preschool children in District 4 of Isfahan. The research method is quasi-experimental and based on a pre-test-post-test design with a control group. To conduct the research, first one area was randomly selected from the six education districts of Isfahan and then two schools were selected as available. After completing the Children Behavior Checklist Questionnaire - Parent Form (CBCL) by parents, 30 couples of parents who reported the most internalization disorders from their children and met the inclusion criteria were selected and asked to participate voluntarily. Cooperation was requested in the training sessions. These numbers were randomly divided into two groups of 15 pairs of experiments and controls. The parents of the experimental group received parenting skills training based on the solution-oriented approach in 6 sessions of 90 minutes. At the end of the sessions, all samples, both experimental and control, who had not received any training, underwent post-test (again, the children-behavioral checklist completed the parent form). Mann-Whitney and Wilcoxon tests were used to analyze the data. Based on the results, in the experimental group compared to the control group in the post-test phase, a significant decrease in the severity of internalization disorders was observed. The results show that all components of pediatric internalization disorders are significantly reduced. Based on the results of the present study, teaching parenting skills to parents with a solution-oriented approach can be an effective method in reducing internalization disorders in preschool children.