Detection of key texts from Tweets in port systems
Charles Guillaume, Cecilia Nunez, Claudia Durán, Raúl Carrasco, Diego Fuentealba · 2021 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON) · 2021
Social media data is a rich source of information to analyze and detect potential problems from people. This work extracts Twitter’s data related to two complex logistics companies to identify words, which can affect the strategy of ports. These words should enhance the business decision-making process to reduce social risks. The literature review suggested that TF-IDF and Latent Dirichlet Allocation can analyze the case studies. The results show that social networks can be linked to sustainable business aspects such as port planning and operations, information management, city, pandemic, ocean, culture, and people’s beliefs.