Constructing Colloquial Dataset for Persian Sentiment Analysis of Social Microblogs

Introduction: Microblogging websites have massed rich data sources for sentiment analysis and opinion mining. In this regard, sentiment classification has frequently proven inefficient because microblog posts typically lack syntactically consistent terms and representatives since users on these social networks do not like to write lengthy statements. Also, there are some limitations to low-resource languages. The Persian language has exceptional characteristics and demands unique annotated data and models for the sentiment analysis task, which are distinctive from text features within the English dialect. Method: This paper first constructs a user opinion dataset called ITRC-Opinion by collaborative environment and insource way. Our dataset contains 60,000 informal and colloquial Persian texts from social microblogs such as Twitter and Instagram. Second, this study proposes a new deep convolutional neural network (CNN) model for more effective sentiment analysis of colloquial text in social microblog posts. The constructed datasets are used to evaluate the presented model. Furthermore, some models, such as LSTM, CNN-RNN, BiLSTM, and BiGRU with different word embeddings, including Fasttext, Glove, and Word2vec, investigated our dataset and evaluated the results. Results: The results demonstrate the benefit of our dataset and the proposed model (72% accuracy), displaying meaningful improvement in sentiment classification performance

The effect of thinking distraction on anxiety of patients during extracorporeal shock wave lithotripsy

Introduction: The aim of this study was to determine the effect of thinking distraction on the anxiety severity in patients undergoing extracorporeal shock wave lithotripsy in the ESWL department of Ayatollah Kashani hospital in Shahrekord. Methods: This is a clinical trial study that was conducted in 2018 in 120 patients referred to Ayatollah Keshāni Hospital in Shahrekord for the purpose of extracorporeal shock wave lithotripsy. Patients were selected through convenience sampling and divided into experimental and control groups  in a quasi-random method. In addition to routine care, the test group received the natural sound of the event along with its beautiful scenery, and the control group received routine care only. The patientchr('39')s anxiety was measured based on the Spielberger questionnaire. The collected data were analyzed using SPSS software, descriptive statistics and t test. Results: Mean anxiety score changes in distraction receiver group, - 21/56± 98   and in the control group was -5/21± 8/12. There was a significant difference (p = 0.001) between the control group and group receiving the thinking distraction  . Conclusion: distraction method is effective in reducing anxiety in patients undergoing extracorporeal lithotripsy and can be used to manage pain in the future