درخت حوزه‌های تخصصی

What is clear is that judges usually judge cases based on their knowledge, experience, personality, and sentiment. Due to high pressures and stress, it may be difficult for them to carefully examine documents and evidence, which leads to more subjective judgments. Legal judgment prediction with artificial intelligence algorithms can benefit judicial bodies, legal experts, and litigants as well as judges. In this research, we are looking at predicting legal sentences in drug cases involving the purchase, possession, concealment, or transportation of illicit drugs, using machine learning methods, and the effect of sentiment and emotions in case texts on predicting the severity of whipping, fines, and imprisonment. So, the text documents of 6000 Persian drug-related cases were pre-processed and then the translation of the NRC Glossary of Emotions and sentiment was used to give each item a score for positive or negative sentiment and a score for emotion. Then machine learning methods were used for modeling. BERT, TFIDF+Adaboost, and Skipgram+LSTM+CNN methods had the highest accuracy, respectively. Also, evaluation criteria were analyzed in situations where sentiment scores, emotional scores, or both were used in the prediction process along with judicial texts. Finally, it was found that the use of sentiment and emotion scores improves the accuracy of legal judgment predictions for all three types of sentences and that sentiments have a greater impact on the accuracy of legal judgment predictions than emotions

Purpose: The spread of consumption in this day and age has gone so far that today it is considered an indicator of lifestyle and even some  find modern life without consumption meaningless and unthinkable. In this regard, since the consumption of smuggled cosmetics in West Azerbaijan province has an increasing trend, so in this study, the communicative and social determinants and factors affecting the consumption of smuggled cosmetics in West Azerbaijan province are investigated.Method: The research method is an applied type as regards purpose and has been carried out using a survey method.  The statistical population includes citizens over 15 in West Azerbaijan province, 674 of whom have been selected by multi-stage cluster sampling. Data was collected using a questionnaire and research variables are above 0.7, which indicates the acceptable reliability of the variables. Statistical data analysis was done using SPSS and Lisrel software.Findings: The findings showed that the consumption of smuggled cosmetics and toiletry products is more than average among the respondents and the use of domestic media is less than average and the use of foreign and virtual media is above average. The results of explanatory analyses in the quantitative phase of the research showed  the variables of gender (in favor of women), socio-economic status (in a positive direction), rate of using internal media (in a negative direction), rate of using external media (in a positive direction), The use of virtual media (in a positive direction), health literacy (in a negative direction) and tendency towards differentiation (in a positive direction) have a significant impact on the consumption of smuggled cosmetics and toiletries. It is explained that the impact of foreign and virtual media is greater than other variables.Conclusion: As a result of lack of content management and inaccuracy in advertising in the virtual sector and social media, the possibility of emergence and escalation of social issues and all kinds of deviant trends related to consumerism in the field of cosmetics and toiletry products increases. Also, domestic mass media can be effective in reducing the consumption of cosmetics by not broadcasting commercial advertisements at intervals.