Named Entity Recognition (NER) is one of the essential prerequisites for many natural language processing tasks. All public corpora for Persian named entity recognition such as ParsNERCorp and ArmanPersoNERCorpus are based on the Bijankhan corpus, which is originated from the Hamshahri newspaper in 2004. Correspondingly, most of the published named entity recognition models in Persian are specially tuned for the news data and are not flexible enough to be applied in different text categories such as social media texts. In this work, we introduce ParsNER-social, a corpus for training named entity recognition models in the Persian language built from social media sources. This corpus consists of 205, 373 tokens, and their NER tags crawled from social media contents, including 10 Telegram channels in 10 different categories. Furthermore, three supervised methods are introduced and trained based on the ParsNER-social corpus: two conditional random field models as baseline models and one state-of-the-art deep learning model with six different configurations are evaluated on the basis of the proposed dataset. The experiments performed show that the Mono-Lingual Persian models based on Bidirectional Encoder Representations from Transformers (MLBERT) outperform the other approaches on the ParsNER-social corpus. Among the different configurations of the MLBERT models, the ParsBERT+BERT-TokenClass model has obtained an F1-score of 89. 65%.

Introduction: Bullying at school is a type of interpersonal violence that could have serious short-term and long-term consequences for both the bullying and the victimized students. Therefore, it is essential to identify the underlying causes. The present study aimed to explore the relationship between social behavior, social preference, social competence, and bullying behaviors among students by considering the moderating role of gender. . Method: This study was descriptive and correlational. The statistical population included all 13-15-year old students in Kashan. Using cluster sampling, 414 students (202 females & 212 males) were chosen. The participants filled in Illinois Bullying Scale (2001), Warden & Mackinnon social behavior Questionnaire (2003), and Smart and Sanson social Competence Questionnaire (2003), and Sociogram. Results: Pearson correlation coefficients showed that there are significant, negative relationships between bullying with social competence and social behavior and positive correlation between bullying and social rejection. There was no relationship between bullying and social acceptance. Moreover, regression analysis indicates that gender (β =. 17, t=4. 11), social behavior (β =-0. 43, t=-9. 0), and social rejection (β =. 11, t=2. 65) can predict 30% of the variance in the bullying behavior. Furthermore, gender has a moderating role only in the relationship between social rejection and social behavior with bullying behavior. Conclusion: The results suggest the critical importance of competence, social behavior, and social preference in causing bullying behaviors. Hence, bullying behaviors could be decreased by designing and implementing programs to teach social behavior for obtaining a desirable social position among peers and especially reducing social rejection and enhancing social behaviors among male students.

social capital represents the power of norms and the density of social networks in a region. An economic, social factor can influence the decision-makers’ decisions regarding management resources through different strategies. Therefore, companies with higher social capital show less symmetry in the behavior of costs. Consequently, consensual capital prevents managers from making decisions that modify opportunistic resources that cause cost adhesion. Therefore, based on this argument, the present study examines the relationship between social capital and asymmetric costs behavior of companies. For this purpose, three criteria of social, occupational, and political communication were used to measure the social capital of managers. The hypothesis testing was performed using regression analysis of a combined set of data related to 73 companies listed on the Tehran Stock Exchange from 2005 to 2018. Following multivariate regression models, the research findings show that social capital reduces the asymmetric behavior of costs by reducing managers' opportunistic motivations and thus reduces the adhesion of costs in the company. In addition, the result of the second hypothesis is that social capital created through managers' social communication with employees increases management optimism and as a result, the adhesion of costs in the company increases.

The purpose of this research was to anticipate pro-social behavior using social trust and social perspective taking. The statistical population of the study included teachers of all educational levels of Sanandaj city in 2017. in this study 425(230 women and 195 men) techers participated. They were selected based on categorical random sampling method. The participants completed the Pro-social behavior (penner, 2002), social Trust (saffarinia and sharif, 2009) and social Perspective Taking (mohaghegi and et al, 2016) questionnaires. The results of regression analysis showed that three components of social perspective taking variable including perception of the views of others, putting self in the place of others and respect for differences, and two components of social trust variable including cooperative tendencies and honesty can be significantly predict pro-social personality (P≤ 0/05) and explain 17% of variance.