Abstract
The Internet is one of the most widely available services in the world today. With the Internet, people are now looking for reviews on the Internet; more specifically, the social networking services. Within the social network medium, we can identify a suitable service that describes more about a person’s personality as the subject. The growth of social networking popularity has contributed to the increase in information available on social networking services. The flexibility of these services allows writing individual thoughts without restrictions. With the vast information available on social networking sites today, how is it possible to look all of these opinions? How do we know which opinion holds truth? How do we know if someone is not bias based on his writing? Hence, it is seen necessary to filter opinions. In this paper we look at the possibility of using search ranking as a medium of filter opinions by exploring opinion mining methods, social networking candidates and search ranking methods. With existing sentiment analysis techniques, we can obtain opinions that are then ranked against a set of keywords.
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Choong, J.J., Hong, J.L. (2013). Opinion Based Search Ranking. In: Lee, M., Hirose, A., Hou, ZG., Kil, R.M. (eds) Neural Information Processing. ICONIP 2013. Lecture Notes in Computer Science, vol 8227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42042-9_58
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DOI: https://doi.org/10.1007/978-3-642-42042-9_58
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