DomainSenticNet: An Ontology and a Methodology Enabling Domain-Aware Sentic Computing

Abstract

In recent years, SenticNet and OntoSenticNet have represented important developments in the novel interdisciplinary field of research known as sentic computing, enabling the development of a variety of Sentic applications. In this paper, we propose an extension of the OntoSenticNet ontology, named DomainSenticNet, and contribute an unsupervised methodology to support the development of domain-aware Sentic applications. We developed an unsupervised methodology that, for each concept in OntoSenticNet, mines semantically related concepts from WordNet and Probase knowledge bases and computes domain distributional information from the entire collection of Kickstarter domain-specific crowdfunding campaigns. Subsequently, we applied DomainSenticNet to a prototype tool for Kickstarter campaign authoring and success prediction, demonstrating an improvement in the interpretability of sentiment intensities. DomainSenticNet is an extension of the OntoSenticNet ontology that integrates each of the 100,000 concepts included in OntoSenticNet with a set of semantically related concepts and domain distributional information. The defined unsupervised methodology is highly replicable and can be easily adapted to build similar domain-aware resources from different domain corpora and external knowledge bases. Used in combination with OntoSenticNet, DomainSenticNet may favor the development of novel hybrid aspect-based sentiment analysis systems and support further research on sentic computing in domain-aware applications.

Public Perception of Online P2P Lending Applications

“…In the parlance of the knowledge-based approach, also known as the lexicon or rulebased approach, various studies have used the Valence Aware Dictionary and Sentiment Reasoner (VADER) to provide sentiment intensity scores [1,2,14,43,44]. Others have used alternative lexicon-based techniques, such as the ontology Library of Chinese Emotional Vocabulary [31], Linguistic Inquiry and Word Count (LIWC) and WordNet software packages [11,34], snowNLP [43], SentiWordNet [38], TextBlob [42], LSTM (long short-term memory) [44], bidirectional long-term, short-term memory (BiLSMT) [45], and DomainSen-ticNet, which is a hybrid aspect-based sentiment analysis system [46].…”