SenticSpace: Visualizing opinions and sentiments in a multi-dimensional vector space

Cambria, Erik; Hussain, Amir; Havasi, Catherine; Eckl, Chris

Abstract

In a world in which millions of people express their feelings and opinions about any issue in blogs, wikis, fora, chats and social networks, the distillation of knowledge from this huge amount of unstructured information is a challenging task. In this work we build a knowledge base which merges common sense and affective knowledge and visualize it in a multi-dimensional vector space, which we call SenticSpace. In particular we blend ConceptNet and WordNet-Affect and use dimensionality reduction on the resulting knowledge base to build a 24-dimensional vector space in which different vectors represent different ways of making binary distinctions among concepts and sentiments.

Citation

Cambria, E., Hussain, A., Havasi, C., & Eckl, C. (2010). SenticSpace: Visualizing opinions and sentiments in a multi-dimensional vector space. . https://doi.org/10.1007/978-3-642-15384-6_41

• Presentation Conference Type: Conference Paper (Published)
• Conference Name: 14th International Conference, KES: International Conference on Knowledge-Based and Intelligent Information and Engineering Systems 2010
• Start Date: Sep 8, 2010
• End Date: Sep 10, 2010
• Publication Date: 2010
• Deposit Date: Sep 19, 2019
• Pages: 385-393
• Series Title: Lecture Notes in Computer Science
• Series Number: 6279
• Series ISSN: 1611-3349
• ISBN: 978-3-642-15383-9
• DOI: https://doi.org/10.1007/978-3-642-15384-6_41
• Keywords: Sentic Computing, AI, Semantic Networks, NLP, Knowledge Base Management, Opinion Mining and Sentiment Analysis
• Public URL: http://researchrepository.napier.ac.uk/Output/1793461