The research project aims to apply an integrated approach to natural language processing NLP to satisfaction surveys. It will focus on understanding and extracting relevant information from survey responses, analyzing feelings, and identifying recurring word patterns. NLP techniques will be used to determine emotional polarity, classify responses into positive, negative, or neutral categories, and use opinion mining to highlight participants opinions. This approach will help identify the most relevant aspects for participants and understand their opinions in relation to those specific aspects. A key component of the research project will be the analysis of word patterns in satisfaction survey responses using NPL. This analysis will provide a deeper understanding of feelings, opinions, and themes and trends present in respondents responses. The results obtained from this approach can be used to identify areas for improvement, understand respondents preferences, and make strategic decisions based on analysis to improve respondent satisfaction.

翻译：本研究项目旨在将一种集成的自然语言处理（NLP）方法应用于满意度调查。其重点在于理解和提取调查回复中的相关信息，分析情感，并识别重复出现的词汇模式。将采用NLP技术来确定情感极性，将回复分类为正面、负面或中性类别，并利用意见挖掘来突出参与者的观点。该方法将有助于识别对参与者最为相关的方面，并理解他们针对这些特定方面的看法。研究项目的一个关键组成部分是使用NLP分析满意度调查回复中的词汇模式。这项分析将更深入地理解受访者回复中所蕴含的情感、观点以及呈现的主题和趋势。通过该方法获得的结果可用于识别待改进的领域，了解受访者的偏好，并基于分析结果做出旨在提升受访者满意度的战略决策。