Introduction: Ethical living is a lifestyle in which all areas of human existence and work are formed and flow around ethics. That is, a person who wants to live MORALly, in all areas, tries to know the ethical considerations related to that area and follow them in practice and live according to them. The current article is research on the MORAL system of Thomas Aquinas with a focus on examining the nature of the MORAL goal of human life and the MORAL rationality of such a life. Material and Methods: The present review study examined bioethics from the perspective of Thomas Aquinas in a descriptive manner. In order to achieve this goal, articles related to research keywords from Thomson Information Institute, Science Direct and Pub Med were examined and books related to the views of Thomas Aquinas were studied. Conclusion: The results of this study show that according to Thomas Aquinas's view on man, becoming like God and realizing God's image in material life and seeing God in the hereafter is the MORAL goal and eternal happiness of man. Also, Thomas Aquinas believes in the MORAL rationality of such a life from both perspectives-having a reason to live MORALly and the usefulness of such a life.

Background: Anti-immigrant SENTIMENTS are macro-level determinants and may explain why immigrants are treated poorly in some host countries. However, very few studies test whether anti-immigrant SENTIMENTS at the macro level are associated with individual-level outcomes of immigrants, such as their happiness. This is important because, according to marginalization-related diminished returns (MDRs) theory, immigrants show worse-than-expected outcomes because of reduced effects of socioeconomic resources. Aim: Built on a multi-level model of happiness and MDRs theory,we conducted this study to test the association between country-level anti-immigrant SENTIMENTS and individual-level happiness of immigrants across European countries. Methods: For this cross-sectional study, we borrowed data from European Social Survey 2020 (ESS 2020). Participants were recruited from Bulgaria, Czechia, Estonia, Finland, France, Croatia, Hungary, Lithuania, Slovenia, and Slovakia. Participants included 997 immigrants. Age, sex, education, employment (worked in the past week), and self-rated health were control variables. Level of countrylevel anti-immigrant SENTIMENTS was the independent variable. Happiness was the outcome. Linear regression was used for data analysis. Results: There were considerable country-level variations in anti-immigrant sentiment across European countries. There were also considerable variations in immigrants' happiness across countries. Overall, higher levels of anti-immigrant SENTIMENTS in the country were associated with lower levels of immigrants' happiness. The results remained similar without and with control variables, including age, gender, education, employment, and self-rated health. Conclusion: Higher anti-immigrant SENTIMENTS, at the macro level, are associated with a lower level of happiness among immigrants at the individual level. Research should test if reduced opportunities or worse treatment of immigrants explains why country-level anti-immigrant SENTIMENTS contribute to reduced happiness of immigrants.

Introduction: Alternative punishments of imprisonment, which are called as a new approach of the penal system to fight against the negative consequences of prison, have many effects and consequences that need to be investigated. Therefore, in this study, while examining the types of alternative punishments, the MORAL and social effects of the implementation of these punishments have been explored. Materials and Methods: The present study was conducted using an analytical-descriptive method. In this study, in order to provide an appropriate answer to the question presented, by referring to the theoretical bases (books) and articles published in the ISC, Magiran, Civilica, SID and Ensani in the years 2011 to 2023 and with the method of extracting the existing legal provisions, the effectiveness of this type of punishment was also criticized in reaching the intended goals. Conclusion: The results of this study show that with the implementation of such punishments, the level of public trust, the growth of MORALs and social capital in the society will also improve. Therefore, the implementation of these punishments, while reducing the criminal population of prisoners and reforming them, provides better implementation of social justice and improvement of public trust, emotional and financial support for the families of criminals

This article introduces, analyzes, and criticizes the work of Lawrence M. Hinman, Ethics: A Pluralistic Approach to MORAL Theory. Hinman is a Philosopher of Ethics in the multimedia learning. He believes that multiculturalism is important factor of nowadays so the most important responsibility of philosophers of Ethics is prevention of MORAL conflict. The global communication and information in 21st century needs global tolerance and respect of various nations, cultures, and MORALities together because different people and societies have a common human nature and common natural rights that obligate to justice and MORAL relationship between different people and various societies’ beliefs throughout the world. MORAL communication in multiculturalism approach is against racial, gender, national, and ethnic prejudice. Hinman believes in MORAL dialogue and global learning across different cultures. The book of Ethics: A Pluralistic Approach to MORAL Theory has a proper category of new ethical problems, and the candid standpoint of author is considerable. He has a logical method, and in the end of every part of book there are some questions for evaluation of students learning. So this book is proper for the philosophy of ethics in universities.

This research aimed at explaining the effects of psycho-social factors on the altruism of charity school- builders. Research method was correlational, and the sampling method was multi-stage cluster sampling. According to the numbers of variables and Kerjesi-Morgan Table, the sample size was determined as 370 people. The following instruments were used to collect data: Personality tests (Neo), Optimism, Schwartz' General Self- efficacy, Hermance's Achievement Motivation, material values, metaphysics, MORAL autonomy and MORAL SENTIMENTS. Data were analyzed by Pearson correlational matrix and the multivariate regression was analyzed based on a simultaneous model. The research findings showed that there is a significant relationship between various dimensions of personality and the donors' altruism. The characteristics of self-efficacy, optimism and achievement motivation have also a significant relationship with the donors' altruism. Meanwhile, social factors or MORAL autonomy, material values, MORAL SENTIMENTS as well as metaphysic values have a significant relationship with the donors' altruism. According to the calculation of slope coefficient, psychological factors consisted of extroversion, agreement, life orientation and self-efficacy have clarified the donors' altruism. Social factors such as material values, metaphysics and MORAL SENTIMENTS have influenced the donors' altruism.

According to the traditional view about stock return, stock price changes are due to systematic changes in the fundamental values of the firm. However, recent researches suggested that the investor sentiment plays a key role in price determination and explaining time series yields, especially for those stocks which valuations are highly subjective and difficult to arbitrage.This research investigates the impact of the investor SENTIMENTS on stock return of selected portfolios which were sorted by different parameters such as size, price, book-to-market value ratio and institutional ownership ratio during 2002 to 2010. Monthly return for each portfolio was calculated based on monthly return of each company by using equal weight strategy. Finally, the coefficients were estimated by using multivariable regression method on the model as time series. For this purpose, the four factor model of portfolio of market, the firm size, book-market-value ratio and investor sentiment were used in order to explain the return. According to the results of the study, there is a positive meaningful relationship between investor SENTIMENTS and stock return of the companies which have minimum size, book-market-value ratio and institutional ownership ratio.

In the present study, managerial sentiment refers to the pleasant and optimistic feeling of the managers and decision makers in the companies. Optimism can be considered a spiritual state showing ones hope for the future. Talking about a company, it is the manger’ s hope for future of the company. Accordingly, the present study examines effects of the managerial optimism on the relationship between investment and cash flow in the company, as well as the moderating effect of financial constraints on this relationship. To do so, we used data of 150 companies listed in Tehran Stock Exchange from 2011 to 2015, multiple regression, as well as panel data model. The results suggested that the manager’ s optimism cannot have a significant effect on the investment-cash flow relationship; and the financial constraint enhances and signifies the effect of manager’ s optimism on the investment-cash flow relationship.

Typically, when someone wants to buy an online product, he/she reviews the comments and notes written by others about the product. Clearly, it has a profound impact on the person's decision to buy or not to buy the product. Sentiment analysis or opinion mining is one of the hot research topics in computer science. The main purpose of sentiment analysis is to extract opinions of individuals about the characteristics of an entity such as a product. In this research, an unsupervised opinion mining is proposed for Persian products based on implicit feature extraction which is a critical step in sentiment analysis. In most previous studies, statistical information is utilized to create a co-occurrence matrix and determine the implicit features. In this paper, we benefit from syntactic rules and sentiment clustering in conjunction with statistical information to construct an efficient co-occurrence matrix between features and sentiment words. The evaluation results provided on a real-world dataset, extracted from Digikala website, indicates that the proposed method achieves higher recall and precision compared to the previous studies.

Brand community interactions and online customer support have become major platforms of brand sentiment strengthening and loyalty creation. Rapid brand responses to each customer request though inbound tweets in twitter and taking proper actions to cover the needs of customers are the key elements of positive brand sentiment creation and product or service initiative management in the realm of intense competition. In this research, there has been an attempt to collect near three million tweets of inbound customer requests and outbound brand responses of international enterprises for the purpose of brand sentiment analysis. The steps of CRISP-DM have been chosen as the reference guide for business and data understanding, data preparation, text mining, validation of results as well as the final discussion and contribution. A rich phase of text pre-processing has been conducted and various algorithms of sentiment analysis were applied for the purpose of achieving the most significant analytical conclusions over the sentiment trends. The findings have shown that the sentiment of customers toward a brand is significantly correlated with the proper response of brands to the brand community over social media as well as providing the customers with a deep feeling of reciprocal understanding of their needs in a mid-to-long range planning.

In recent years, the growth of social networks and, consequently, the increasing content of these networks have led people to use others’ opinions to make decisions for the purchase and use of products, services or even political choices. Given the fact that users' comments are textual and their reading and summarizing is timely and difficult, the automation of the extraction of opinions and SENTIMENTS of users' comments is one of the suggested solutions for online sales sites to provide more efficient services to customers for better decision making. Sentiment analysis or opinion mining is a process where people's opinions, feelings and attitudes are extracted in relation to a particular subject and are recognized as a branch of the text mining. The results of sentiment analysis can be used in recommender systems to provide more effective shopping suggestions. Information derived from the opinion mining can be used in a variety of fields such as libraries for better choices and purchases based on the users' real opinions. In this research, a system for automatically categorizing the SENTIMENTS expressed in the opinions of the buyers of the Amazon book website is presented. The system is designed using ensemble voting models to analyze the sentiment of Amazon users' comments. For all analyses, Python text mining packages are used. In ensemble method two methods are used: majority voting and weight-based voting. In the weighting method, a greater weight is assigned to a classifier by higher accuracy. By comparing the performance of the results, the weighting model is chosen as the final model for making the sentiment analysis. Results show that the proposed system can automatically classify positive and negative comments with an accuracy of over 80%.