FeatureOnto: A Schema on Textual Features for Social Data Analysis

Sumit Dalal, Sarika Jain, Mayank Dave

Keywords: Deep Learning, Depression, Knowledge Graph, Machine learning, Ontology, Social Data, Twitter

Abstract: Social media is one of the valuable information sources which present much data to the researchers. This information is mainly analyzed by machine learning and the deep learning methods, which lack semantics and interpretation in their outputs. Also, much attention is paid to the feature engineering there. We present a taxonomy of the different feature categories. The categories relate to the features learned during the training for analyzing the textual information, specifically available on social platforms. The ontological view of the data will represent knowledge in a more understandable form besides interpreting the machine learning results for various tasks related to the social data analysis. We chose Depression as the use case purpose. The ontology is designed using Ontology Web Language and Resource Description Framework in the Protégé. The validation of the ontology is carried out with designed competency questions.