SVM Optimization for Sentiment Analysis
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2018, Vol 9, Issue 4
Abstract
Exponential growth in mobile technology and mini computing devices has led to a massive increment in social media users, who are continuously posting their views and comments about certain products and services, which are in their use. These views and comments can be extremely beneficial for the companies which are interested to know about the public opinion regarding their offered products or services. This type of public opinion otherwise can be obtained via questionnaires and surveys, which is no doubt a difficult and complex task. So, the valuable information in the form of comments and posts from micro-blogging sites can be used by the companies to eliminate the flaws and to improve the products or services according to customer needs. However, extracting a general opinion out of a staggering number of users’ comments manually cannot be feasible. A solution to this is to use an automatic method for sentiment mining. Support Vector Machine (SVM) is one of the widely used classification techniques for polarity detection from textual data. This study proposes a technique to tune the SVM performance by using grid search method for sentiment analysis. In this paper, three datasets are used for the experiment and performance of proposed technique is evaluated using three information retrieval metrics: precision, recall and f-measure.
Authors and Affiliations
Munir Ahmad, Shabib Aftab, Muhammad Salman Bashir, Noureen Hameed, Iftikhar Ali, Zahid Nawaz
Keywords
Related Articles
- EP ID EP286410
- DOI 10.14569/IJACSA.2018.090455
- Views 58
- Downloads 0
Novel Altered Region for Biomarker Discovery in Hepatocellular Carcinoma (HCC) Using Whole Genome SNP Array
Cancer represents one of the greatest medical causes of mortality. The majority of Hepatocellular carcinoma arises from the accumulation of genetic abnormalities, and possibly induced by exterior etiological factors espe...
Multimodal Automatic Image Annotation Method using Association Rules Mining and Clustering
Effective and fast retrieval of images from image datasets is not an easy task, especially with the continuous and fast growth of digital images added everyday by used to the web. Automatic image annotation is an approac...
Comparative Study between the Proposed GA Based ISODAT Clustering and the Conventional Clustering Methods
A method of GA: Genetic Algorithm based ISODATA clustering is proposed.GA clustering is now widely available. One of the problems for GA clustering is a poor clustering performance due to the assumption that cluste...
A Comparative Study of Engineering Students Pedagogical Progress
Students’ pedagogical progress plays a pivotal role in any educational institute in order to pursue imperative education. Educational institutes, Universities, Colleges implement various performance measures in order to...
An Empirical Investigation of Predicting Fault Count, Fix Cost and Effort Using Software Metrics
Software fault prediction is important in software engineering field. Fault prediction helps engineers manage their efforts by identifying the most complex parts of the software where errors concentrate. Researchers usua...