Natural Language Processing and Social Network Analysis
The knowledge is one of the outcomes of the humankind, and it is encoded in natural language, which is the main communication means of humans. The research line Natural Language Processing and Social Networks (NLP+SR) aims to enable computers to access to human knowledge by means the understanding and generation of language. The underlying information of social networks from the human interaction complements the human knowledge. The combination of the knowledge from natural language and social networks allows to face up to diverse AI challenges, such as: the representation of knowledge for common sense reasoning, using natural language to explain the outputs and behaviour of machine learning algorithms and the understanding and generation of language.
The NLP+RS research line aims to study the computational methods for transforming the unstructured data nature of natural language and social networks to structured data, which may be processed by computers. Also, we will study the last advances on machine learning and deep learning for processing those data and generating high level knowledge. Specifically, the research line PLN+RS will work on:
- Sentiment and Emotion Analysis.
- Misinformation and fake news analysis.
- Question and Visual Question Answering.
- Information Extraction
- Monolingual, multilingual and crosslingual analysis.
- Summarisation of information.
- Text classification.
- Text Mining in Social Networks.
- Natural Language Processing for Decision Making.
All these task can be applied to the domain of healthcare; knowledge acquisition from user data for the industry; brand reputation analysis; information gathering and high-level knowledge generation.
Contact: Eugenio Martínez Cámara
|Cobo Martín, Manuel Jesús||manueljesus.cobo@uca.PxMxe4RpKs9jes||DaSCI Technology Applications Area||PhD|
|Luzón García, María Victoria||luzon@uPsd8usCthRgr.es||DaSCI Technology Applications Area||PhD|