A Machine Learning Approach to Extract Opinions from Social Media Content

  • Authors

    • Salina Adinarayana
    • E Ilavarasan
    https://doi.org/10.14419/ijet.v7i4.5.20080

    Received date: September 22, 2018

    Accepted date: September 22, 2018

    Published date: September 22, 2018

  • LDA, Latent Dirichlet Allocation, Opinion Mining (OM), CISDL, Mobile platform, social media content

  • Abstract

    The Opinion Mining (OM) from mobile based social media content (SMC) is more challenging compared to topic-based mining, and it cannot be performed based on just examining the presence of single words in the text containing opinion expressions. Moreover, the existing systems of opinion   classification find that a large number of features that are not feasible for the mobile environment. The existing methods of OM in this mobile environment do not consider the semantic orientation of the SMC in the review. The proposed machine learning approach extends the feature-based classification approach to identify the orientation of the phrase on taking context into account to improve the accuracy. 

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  • How to Cite

    Adinarayana, S., & Ilavarasan, E. (2018). A Machine Learning Approach to Extract Opinions from Social Media Content. International Journal of Engineering and Technology, 7(4.5), 257-261. https://doi.org/10.14419/ijet.v7i4.5.20080