This paper describes the SemEval 2016 shared task on Aspect Based Sentiment Analysis (ABSA), a continuation of the respective tasks from 2014 and 2015. In its third year, the task provided 19 training and 20 testing datasets for 8 languages and 7 domains, as well as a common evaluation procedure. The task attracted 245 submissions from 29 teams. The paper outlines the task setup, datasets, annotation process, evaluation measures, and baselines. It also discusses the participation and evaluation results, highlighting the performance of different systems and the challenges in aspect-based sentiment analysis. The introduction emphasizes the importance of ABSA in understanding consumer experiences and business feedback, and the paper concludes with a discussion of future directions, including the creation of datasets in more languages and domains.This paper describes the SemEval 2016 shared task on Aspect Based Sentiment Analysis (ABSA), a continuation of the respective tasks from 2014 and 2015. In its third year, the task provided 19 training and 20 testing datasets for 8 languages and 7 domains, as well as a common evaluation procedure. The task attracted 245 submissions from 29 teams. The paper outlines the task setup, datasets, annotation process, evaluation measures, and baselines. It also discusses the participation and evaluation results, highlighting the performance of different systems and the challenges in aspect-based sentiment analysis. The introduction emphasizes the importance of ABSA in understanding consumer experiences and business feedback, and the paper concludes with a discussion of future directions, including the creation of datasets in more languages and domains.