ABSTRACT
‘Sentiment analysis has had a rise in popularity as a research field due to social media and the volumes of opinionated data shared through them. Also an emerging trend brought about by big data is the development of database management systems that deviate from the relational DBMS structure, such as the NoSQL DBMSs. This paper investigates the processing of sentiments of opinionated restaurant-related text that are stored in MongoDB, a NoSQL DBMS, and compares them to processing text on OS-managed text files. In connection with this, the paper also discusses the construction of a user interface that displays sentiment analysis in real-time. Results shown by the finished software highlight the faster performance of processing data in MongoDB over text files in searching restaurant-related tweets, especially when querying for multiple restaurants is done in parallel.
