Opinion Mining (OM) or Sentiment Analysis (SA) can be defined as the task of detecting, extracting and classifying opinions on something. It is a type of the processing of the natural language (NLP) to track the public mood to a certain law, policy, or marketing, etc. It involves a way that development for the collection and examination of comments and opinions about legislation, laws, policies, etc., which are posted on the social media. The process of information extraction is very important because it is a very useful technique but also a challenging task. This is focused to extract sentiment from an object in the web-wide, need to automate opinion-mining systems to do it. The existing techniques for sentiment analysis include machine learning (supervised and unsupervised), and lexical-based approaches.
PUBLICATIONS
JOURNALS
- Gunawardana, S.A.A., Arooz, F.R., Peramunugamage, A. and Halwatura, R.U. (2020) ‘Critical analysis of lecturer’s perception on integrating concepts of sustainability in university curricular’ ,Integrated Science Education Journal, Accepted Manuscript.
INTERNATIONAL COLLABORATIONS
- BECK: Integrating education with consumer behavior relevant to energy efficiency and climate change at the Universities of Russia, Sri Lanka and Bangladesh (2019-2022), Funded by EU Erasmus+ grant scheme. Aimed developing MOOC modules for BSc and MSc curriculum on energy efficiency and climate change.
ONGOING RESEARCH
- Decision making model for energy efficient applications in green buildings.
- Investigation on development of an educational model to enhance knowledge on sustainability applications in buildings.