Research into NLP Techniques for Analysis and Monitoring of Social Media Dynamics

The bachelor thesis is devoted to the research into topical issues of using Natural Language Processing (NLP) techniques for analysis and monitoring of Social Media dynamics. The first chapter serves as an overview of key definitions, concepts, and classification of Social Media, describes the main applications of Social Media, as well as examines the role of Social Media Analysis for business issues in detail. The second chapter describes NLP techniques application for Social Media Analysis (including analysis of possible restrictions) along with methodological and technological aspects of Sentimental Analysis. The third chapter introduces a practical example of fine-tuning the pre-trained model BERT (Bidirectional Encoder Representations from Transformers) for two tasks: Aspect Extraction and Aspect Sentiment Classification. The work is of interest both for researchers involved in the development of the theoretical foundations in the field of Natural Language Processing, as well as for marketing specialists involved in Sentimental Analysis in the field of Social Media.