Cross-Lingual Sentiment Classification from English to Arabic using Machine Translation
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2017, Vol 8, Issue 12
Abstract
Cross-lingual sentiment learning is becoming increasingly important due to the multilingual nature of user-generated content on social media and the scarce resources for languages other than English. However, cross-lingual sentiment learning is a challenging task due to the different distribution between translated data and original data and due to the language gap, i.e. each language has its own ways to express sentiments. This work explores the adaptation of English resources for sentiment analysis to a new language, Arabic. The aim is to design a light model for cross-lingual sentiment classification from English to Arabic, without any manual annotation effort which, at the same time, is easy to build and does not require deep linguistic analysis. The ultimate goal is to find an optimal baseline model and to determine the relation between the noise in the translated data and the accuracy of sentiment classification. Different configurations of several factors are investigated including feature representation, feature reduction methods, and the learning algorithms to find the optimal baseline model. Experiments show that a good classification model can be obtained from translated data regardless of the artificial noise added by machine translation. The results also show a significant cost to automation, and thus the best path to future enhancement is through the inclusion of language-specific knowledge and resources.
Authors and Affiliations
Adel Al-Shabi, Aisah Adel, Nazlia Omar, Tareq Al-Moslmi
Keywords
Related Articles
- EP ID EP259593
- DOI 10.14569/IJACSA.2017.081257
- Views 102
- Downloads 0
Enhanced Security for Data Sharing in Multi Cloud Storage (SDSMC)
Multiple Cloud storage has become one of the essential services of cloud computing. This Multi-Cloud storage models allow users to store sliced encrypted data in various cloud drives. Thus, it provides support for variou...
From Emotion Recognition to Website Customizations
A computer vision system that recognizes the emotions of a website’s user and customizes the context and the presentation of this website accordingly is presented herein. A logistic regression classifiers is trained over...
A Novel Mapreduce Lift Association Rule Mining Algorithm (MRLAR) for Big Data
Big Data mining is an analytic process used to discover the hidden knowledge and patterns from a massive, complex, and multi-dimensional dataset. Single-processor's memory and CPU resources are very limited, which makes...
A Novel Efficient Forecasting of Stock Market Using Particle Swarm Optimization with Center of Mass Based Technique
This paper develops an efficient forecasting model for various stock price indices based on the previously introduced particle swarm optimization with center mass (PSOCOM) technique. The structure used in the proposed pr...
To Generate the Ontology from Java Source Code
Software development teams design new components and code by employing new developers for every new project. If the company archives the completed code and components, they can be reused with no further testing unlike th...