Social media is an inseparable part of human life, although published information through social media is not always true. rumors may spread easily and quickly in the social media, hence, it is vital to have a tool for rumor veracity detection. Papers already proved that users’ stance is an important tool for this goal. To the best knowledge of authors, so far, no work has been proposed to study the ordering of users’ stances to achieve the best possible accuracy. In this work, we have investigated the importance of the stances ordering in the efficiency of rumor veracity detection. This paper introduces a concept called trust for stance sequence ordering and shows that proper definition of this function can significantly help improve to improve veracity detection. The paper examines and compares different modes of definition of trust. Then, by choosing the best possible definition, it was able to outperform state-of-the-art results on a well-known dataset in this field, namely SemEval 2019.

Mysticism is one of the constructive desires in man’s nature, concerned about man’s spiritual welfare. It is man’s enthusiasm for attaining spiritual elevation that has brought about his special attention to mysticism; however, this tendency has to originate from its genuine sources, be immune from extremes and act in conformity with the criteria of perfect man. Nevertheless, the course of these qualities have occasionally been perverted by the pretenders, and as a result, they have been driven toward destructive desires. The present article not only studies the exigency and key role of mysticism in the way of man’s soul elevation, but also introduces its genuine sources and the criteria of constructive mysticism based on the Islamic teachings and elaborates on the outlook and practical manner of Imam Khomeini, as a sample of grand muslim mystic.

Semantics is part of today's linguistics and is the knowledge of meaning analysis, examining different types of meaning in order to specify the precise one, in and out of a context. What matters in this science is the evolution of word from the beginning to the contemporary period and discovery of a contextual meaning of a word, indeed. The present research studies the contextual meaning of truth and sincerity in Nahj al-Balagha and attempts to find out its semantic status based on descriptive semantic methodology. The study indicates that first of all, this word has not undergone fundamental changes in its meaning and implication over time and it has always been considered as a moral virtue. Moreover, in Nahj al-Balagha, it carries the original (literal) and idiomatic meaning and it collocates with words such as faith, benefaction, and right and … in a semantic network and in a semantics confrontation with it has appeared falsehood. Its semantic domain also includes three domains of truth and sincerity of belief, moral truth and truth as a general concept.

During the last few years, rumor and its rapid diffusion via social media have affected public opinions, even in some important such as presidential elections. One of the main approaches for rumor detection methods is based on content and natural language processing. Despite considerable improvement made in this regard in the English language, unfortunately, we have not witnessed enough progress in the Persian language, mainly due to a lack of datasets in this area. The main novelty of this paper is combining different learning methods to consider the classification problem from different aspects and combine the classifiers’ results to achieve a reasonable final result. In the proposed method, each classifier is assigned a weight depending on its f-measure value; thus, the final fused result is closer to the performance of the best classifier. When news samples have various characteristics, and the best classifier is not predetermined, this fusion method is more beneficial. Therefore, as the conclusion of this research, compared to a single rumor detection method, the fusion of classifiers could be used to achieve better results when the news samples have various characteristics.

Purpose: Purpose: The main objective of this research is to present a model for managing rumors in Islamic Azad University. Design/ Methodology/ Approach: the present study has a mixed Approach, Its qualitative part is done using the content analysis method (Theme) and subsequent sections based on the identified model in the qualitative section. In the qualitative section, the theoretical foundations of the subject and the semi-structured interviews were used, so that with 15 people from the various classes (Chairmanship, from the free and semi-structured interviews, the deputy and managers of the group and professors) from the free and semi-structured interviews were conducted using the theme analysis method, main Themes, and refining and refining. In the quantitative Section, a questionnaire was designed based on the main themes extracted and validated by experts by cronbach's alpha, and were selected by 384 individuals working at free college. And the confirmatory factor analysis and AHP was applied in the quantitative Section. Research Findings: The result of the interview and coding showed that the rumor management had 8 core themes (Managerial skills, Ethics, behavioral factors, organizational factors, personality traits, shared values, leadership), and 31theme of the rumor management model was developed through the hierarchical tree and in the quantitative section was approved by the structural equations method of validity and validity of the obtained model, and the themes weights were determined. Central Tehran Branch has the highest score (0. 971) from other units in terms of rumor management relative to other units of the islamic free university. Limitations & Consequences: the limitation of this study is the lack of interviews with the Chairman, deputy director of the entire central organization for the richness of the results. Practical Consequences: The model presented in this research helps managers to use their managerial skills to manage rumor Management. Innovation or value of the Article: this study investigates effective factors on rumor management and a model for management in the Univerity's work Environment.

Background: The spreading of health-related rumors can profoundly put society at risk, and the investigation of strategies and methods can efficiently prevent the dissemination of hazardous rumor is necessary, especially during a public health emergency including disease outbreaks. In this article we review the studies that implicated the surveillance system in identifying rumors and discuss the different aspects of current methods in this field. Methods: We searched PubMed, EMBASE, Scopus, and Web of Science databases for relevant publications in English from 2000 to 2020. The PICOS approach was used to select articles, and two reviewers extracted the data. Findings were categorized as a source of rumors, type of systems, data collection, and data transmission methods. The quality of the articles was assessed using the Mixed Method Appraisal Tool (MMAT) checklist. Results: Five studies that presented the methods used for rumor detection in different outbreaks were included in the critical appraisal process. Findings were grouped into four categories: source of rumors, type of systems, data collection, and data transmission methods. The source of rumors in most studies was media, including new social and traditional media. The most used data collection methods were human-computer interaction technique, and automatic and manual methods each were discussed in one study. Also, the data transmission method was asynchronous in the majority of studies. Conclusion: Based on our findings, the most common rumor detection systems used in the outbreaks were manual and/or human-computer methods which are considered to be timeconsuming processes. Due to the ever-increasing amount of modern social media platforms and the fast-spreading of misinformation in the times of outbreaks, developing the automatically and real-time tools for rumor detection is a vital need.

When every news item is posted on social media, reactions to it are different and arouse curiosity from different viewpoints. The most important part is to understand the accuracy of the news. A rumor is invalid news, meaning it has not yet been confirmed and it may cause irreparable damage if it is not valid. Therefore, it is very important to detect it. rumor detection, or in other words, determining its validity, plays an essential role in preventing fake news. Naturally, every phenomenon of normal and anomaly is transmitted to people through social networks. Every News Reactions to that news are different. Depending on the importance of the news, it may be widely covered or it may not have a specific reaction. But if the news spreads widely, it arouses curiosity from different angles. The news is false or true, or the news is valid or invalid. In this work, an attempt was made to identify rumors on social networks by using Hand-Crafted features based on tweets, users and a combination of the two, oversampling and normalization, and by using machine learning classification. Using 4 machine learning classifiers, including Support vector machine, Logistic regression, K-nearest neighbors and Random forest, the two rumors on social networks were detected. Two data sets, PHEME 2017 and PHEME 2018, have been used. The results on these two datasets show that in PHEME 2017, the random forest classifier shows an accuracy of 0.988 using tweet and combination features. Also, these features show a precision of 0.987, which is better than other classifiers used in this work. This classifier has a better recall than other classifiers along with logistic regression with a value of 0.986. Also, this classifier obtained better results with the two mentioned features, with 0.987. In the PHEME 2018 dataset, it obtained the RF classifier with an accuracy of 0.969 using tweet and combination features, and it has better performance in precision, recall and F1. In addition, the user feature in the classifier of k nearest neighbors brings better results than the other two features.

rumors and the spread of false reports is one of the issues dealt with in the Holy Quran and narrations from the Imams (a.s.). A rumor is a false story that circulates in the community easily. It is used to distort facts related to the outstanding individuals and celebrities. Also, rumors are widely utilized in soft war and psychological operations. Significance and ambiguity are the two basic principles on the basis of which rumors are created. In other words, rumors are created about those things to which the audience are sensitive and this sensitivity as well as ambiguity paves the way for their spread. There are different types of rumors: 1) rumors against the Prophet’s character including such titles as a) a poet, lunatic, enchanter, enchanted and liar; b) betrayal rumors; c) injustice rumors; d) rumors related to the naivety and simplemindedness of the Prophet (p.b.u.h.); 2) rumors against the Prophet’s family (sexual and moral rumors) represented in the efk tale; 3) rumors related to the security issues of the society (military, social and political rumors) which were often spread by simple-minded Muslims with weak faith. The last category of rumors were spread under the influence the hypocrites’ remarks and mainly contained reports about battles including the rumors related to the Ohod Battle (e.g. the rumor of the Prophet’s (p.b.u.h.) martyrdom, the Tabuk Battle (e.g. the defeat of the Army of Islam) and the Ahzab Battle.According to Islam, to maintain individual health, it is necessary to maintain the health of society. Hence, Islam strongly disapproves of rumor-mongers and the Holy Quran considers rumor a great sin and warns that rumor-makers and rumor-mongers will be punished in this world and in the hereafter.