With the exponential growth of social media platforms, vast amounts of data are generated daily, capturing public opinions, sentiments, and trends in real time. Automatic sentiment analysis using Natural Language Processing (NLP) has emerged as an essential tool to process this data, helping industries, researchers, and policymakers understand social sentiment more effectively. This study explores various NLP techniques for sentiment analysis, including machine learning-based, lexicon-based, and deep learning models. By examining advancements in NLP algorithms and challenges related to language diversity, slang, and context in social media data, this paper highlights the strengths and limitations of current methodologies and discusses potential future directions.

The European Union is the world's largest importer of desiccated coconut products with the six main import destinations being the Netherlands, Germany, the UK, Poland, Belgium and France. Despite ups and downs in the last five years, Indonesia's exports of desiccated coconut products have increased again in 2021. To determine the competitiveness and development potential of dessicated coconut products to six major markets in the European Union, this study used the RCA and EPD methods. The results show that all six countries are highly competitive for Indonesian dessicated coconut exports. France is an optimistic market for export development. Potential markets for export development are the Netherlands, Germany, the UK and Belgium.