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Toward Developing A Mining Opinion Model:Conceptual FrameworkAbstract: Opinion mining or as called sentiment analysis, its study of public opinions, attitude, emotions, sentiment towards specific issues or targets computationally. People most likely prefer to discuss and express their own opinion or feeling publicly behind the PC screen through social media net- works such as twitter, Facebook, flickers…etc. This huge amount of opinions or sentiments that travel though social media networks everywhere give us important indicator to understand human behaviour and how it’s can predict the use satisfaction. Opinion mining/sentiment analysis consider one of the most active research sector in natural language processing, data mining, information retrieval, and Web mining. Recently, many re- searches have spread to wide spectrum areas like business and management sciences, political sciences and social sciences. This paper review will have proposed initial mining opinion model that would be first stage in improving recommendation and supporting system quality. This paper design as following, section one: An introduction, section two: method and the applied theories, section three an initial mining opinion model proposal, last section is the conclusion

Author

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  • Rawia Tahrir Salih Mohammed

    (Faculty of Computer Science and Information Technology,University Putra Malaysia)

  • Rusli Haji Abdullah

    (Faculty of Computer Science and Information Technology,University Putra Malaysia)

Abstract

No abstract is available for this item.

Suggested Citation

  • Rawia Tahrir Salih Mohammed & Rusli Haji Abdullah, 2018. "Toward Developing A Mining Opinion Model:Conceptual FrameworkAbstract: Opinion mining or as called sentiment analysis, its study of public opinions, attitude, emotions, sentiment towards specific issu," Acta Informatica Malaysia (AIM), Zibeline International Publishing, vol. 2(2), pages 17-18, January.
    • Handle: RePEc:zib:zbnaim:v:2:y:2018:i:2:p:17-18
    DOI: 10.26480/aim.02.2018.17.18
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    References listed on IDEAS

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    1. William H. DeLone & Ephraim R. McLean, 1992. "Information Systems Success: The Quest for the Dependent Variable," Information Systems Research, INFORMS, vol. 3(1), pages 60-95, March.
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