In the context of the ongoing forth industrial revolution and fast computer science development the amount of textual information becomes huge. So, prior to applying the seemingly appropriate methodologies and techniques to the above data processing their nature and characteristics should be thoroughly analyzed and understood. At that, automatic text processing incorporated in the existing systems may facilitate many procedures. So far, text classification is one of the basic applications to natural language processing accounting for such factors as emotions’ analysis, subject labeling etc. In particular, the existing advancements in deep learning networks demonstrate that the proposed methods may fit the documents’ classifying, since they possess certain extra efficiency; for instance, they appeared to be effective for classifying texts in English. The thorough study revealed that practically no research effort was put into an expertise of the documents in Vietnamese language. In the scope of our study, there is not much research for documents in Vietnamese. The development of deep learning models for document classification has demonstrated certain improvements for texts in Vietnamese. Therefore, the use of long short term memory network with Word2vec is proposed to classify text that improves both performance and accuracy. The here developed approach when compared with other traditional methods demonstrated somewhat better results at classifying texts in Vietnamese language. The evaluation made over datasets in Vietnamese shows an accuracy of over 90%; also the proposed approach looks quite promising for real applications.

The European Union-Vietnam Free Trade Agreement (EVFTA), taking effect on August 2020,  was expected to bring strategic benefits for Vietnam with one of its largest and most important partners. However, the United Kingdom, a leading economy within the EU, was left the EU on the January of the same year. The new free trade aggrement between UK and Vietnam, known as UKVFTA, was signed with the hope to avoid missing any benefits that the EVFTA had promised. This paper aims to identify and analyze the impact of the two aggrements, EVFTA and UKFTA on Vietnam-EU’s and Vietnam-UK trades under the negative effects of the Covid-19 pandemic. A compehensive analysis of the trade between Vietnam and the two mentioned partners for two year before and two year after the agrrement was made to carry out the positive effects of the contracts. The secondary data were taken from the World Bank, ADB and Vietnam Office of Statistics. The results showed that, the two aggrements successfully brought about higher surpluses for Vietnam trade, despite the fact that the overall of Vietnam trade are mostly deficit during the four examined years. The results would be helpful to evaluate free trade agreements for overcoming the negative impact of the Covid-19 pandemic for Vietnam and other developing countries.