Context-Sensitive Opinion Mining using Polarity Patterns

Abstract

The growing of Web 2.0 has led to huge information is available. The analysis of this information can be very useful in various fields. In this regards, opinion mining and sentiment analysis are one of the most interesting task that many researchers have paid attention for two last decades. However, this task involves to some challenges that a very important challenge is the different polarity of words in various domain and context. Word polarity is an important feature in the determination of review polarity through sentiment analysis. Existing studies have proposed n-gram technique as a solution which allows the matching of the selected words to the lexicon. However, identification of word polarity using the standard n-gram method poses limitation as it ignores the word placement and its effect according to the contextual domain. Therefore, this study proposes a linguistic-based model to extract the word adjacency patterns to determine the review polarity. The results reflect the superiority of the proposed model compared to other benchmarking approaches.

Authors and Affiliations

Saeedeh Sadidpour, Hossein Shirazi, Nurfadhlina Sharef, Behrouz Minaei-Bidgoli, Mohammad Sanjaghi

Keywords

Related Articles

Variability Management in Business-IT Alignment: MDA based Approach

The expansion of PAIS (Process Aware Information Systems) has created the need for reuse in business processes. In fact, companies are left with directories containing several variants of the same business processes, whi...

Research Pathway towards MAC Protocol in Enhancing Network Performance in Wireless Sensor Network (WSN)

The applications and utility of Wireless Sensor Network (WSN) have increased its pace in making an entry to the commercial market since the last five years. It has successfully established its association with Internet-o...

Web Service for Incremental and Automatic Data Warehouses Fragmentation

The data warehouses (DW) are proposed to collect and store heterogeneous and bulky data. They represent a collection of thematic, integrated, non-volatile and histories data. They are fed from different data sources thro...

EFFICIENT ROLE ASSIGNMENT SCHEME FOR MULTICHANNEL WIRELESS MESH NETWORKS

A wireless mesh network (WMN) is cost-effective access network architecture. The performance of multi-hop communication quickly reduces as the number of hops becomes larger. Nassiri et al. proposed a Molecular MAC protoc...

A Strategy for Training Set Selection in Text Classification Problems

An issue in text classification problems involves the choice of good samples on which to train the classifier. Training sets that properly represent the characteristics of each class have a better chance of establishing...

Download PDF file
  • EP ID EP90984
  • DOI 10.14569/IJACSA.2016.070920
  • Views 147
  • Downloads 0

How To Cite

Saeedeh Sadidpour, Hossein Shirazi, Nurfadhlina Sharef, Behrouz Minaei-Bidgoli, Mohammad Sanjaghi (2016). Context-Sensitive Opinion Mining using Polarity Patterns. International Journal of Advanced Computer Science & Applications, 7(9), 145-150. https://europub.co.uk/articles/-A-90984