Articles

Sentiment analysis, a vital aspect of natural language processing, involves the application of machine learning models to discern the emotional tone conveyed in textual data. The use case for this type of problem is where businesses can make informed decisions based on customer feedback, identify the sentiments of their employees, and make decisions on hiring or retention, or for that matter, classify a text based on its topic like whether it is about a particular subject like physics or chemistry as is useful in search engines. The model leverages a sequential architecture, transforms words into dense vectors using an Embedding layer, and captures intricate sequential patterns with two Long Short-Term Memory (LSTM) layers. This model aims to effectively classify sentiments in text data using a 50-dimensional embedding dimension and 20 % dropout layers. The use of rectified linear unit (ReLU) activations enhances non-linearity, while the SoftMax activation in the output layer aligns with the multi-class nature of sentiment analysis. Both training and test accuracy were well over 80%.

The purpose of this study was to investigate the key role of service quality and beauty of sports facilities in increasing customer satisfaction. The research method is descriptive and correlational research. The statistical population of the study was 154188 organized athletes covered by sports insurance (103890 men, 50298 women) who were working in sports halls of Mazandaran province and according to Morgan table, 384 athletes were randomly selected by cluster Were. Aesthetic questionnaire, service quality and customer satisfaction were used to collect information. Data analysis was performed using Pearson test and structural equation modeling by SPSS24 and Amos structure analysis software. According to the research results, the indirect effect of aesthetics of sports venues on increasing customer satisfaction through service quality is significant. Managers can take effective steps to increase their presence and increase the income of gyms by using quality improvement strategies and customer satisfaction.