ABSA toolkit: an open source tool for aspect based sentiment analysis

Author Affiliation

Zarmeen Nasim is Lecturer at Institute of Business Administration (IBA), Karachi

Sajjad Haider is Professor at Institute of Business Administration (IBA), Karachi

Faculty / School

Faculty of Computer Sciences (FCS)


Department of Computer Science

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Document Type


Source Publication

International Journal on Artificial Intelligence Tools




Artificial Intelligence and Robotics | Computer Sciences


With a rapid increase in e-commerce websites, people are often interested in analyzing customer reviews expressing customer sentiments on different features of a product before making purchase decisions. In this paper, we present ABSA (Aspect-Based Sentiment Analysis) Toolkit developed for performing aspect-level sentiment analysis on customer reviews. The system has two main phases: (a) development phase and (b) production phase. The development phase allows a user to train models for performing aspect level sentiment analysis tasks on the target domain. In the production phase, a web application is provided through which an end user can submit reviews to analyze aspect level sentiments. The system is built using state-of-the-art approaches of aspect term extraction, aspect category detection, and aspect polarity identification. To the best of our knowledge, there is no framework publicly available to build aspect-level sentiment analysis application. All the source code of the ABSA toolkit is available on GitHub.

Indexing Information

HJRS - X Category, Scopus, Web of Science - Science Citation Index Expanded (SCI)

Publication Status