Memorias de investigación
Communications at congresses:
Mining the Opinionated Web: Classification and Detection of Aspect Contexts for Aspect Based Sentiment Analysis
Year:2016

Research Areas
  • Telematics

Information
Abstract
Aspect Based Sentiment Analysis (ABSA) provides further insight into the analysis of social media. Understanding user opinion about different aspects of products, services or policies can be used for improving and innovating in an effective way. Thus, it is becoming an increasingly important task in the Natural Language Processing (NLP) realm. The standard pipeline of aspect-based sentiment analysis consists of three phases: aspect category detection, Opinion Target Extraction (OTE) and sentiment polarity classification. In this article, we propose an alternative pipeline: OTE, aspect classification, aspect context detection and sentiment classification. As it can be observed, the opinionated words are first detected and then are classified into aspects. In addition, the opinionated fragment of every aspect is delimited before performing the sentiment analysis. This paper is focused on the aspect classification and aspect context detection phases and proposes a twofold contribution. First, we propose a hybrid model consisting of a word embeddings model used in conjunction with semantic similarity measures in order to develop an aspect classifier module. Second, we extend the context detec- tion algorithm by Mukherjee et al. to improve its performance. The system has been evaluated using the SemEval2016 datasets. The evaluation shows through several experiments that the use of hybrid techniques that aggregate different sources of information improves the classification performance.
International
Si
Congress
IEEE ICDM SENTIRE
960
Place
Barcelona
Reviewers
Si
ISBN/ISSN
2375-9259
10.1109/ICDMW.2016.0132
Start Date
12/12/2016
End Date
15/12/2016
From page
900
To page
907
2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW)
Participants

Research Group, Departaments and Institutes related
  • Creador: Departamento: Ingeniería de Sistemas Telemáticos