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Cluster Computing

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15.12.2017

Predicting user preferences on changing trends and innovations using SVM based sentiment analysis

verfasst von: K. Chidambarathanu, K. L. Shunmuganathan

Erschienen in: Cluster Computing | Sonderheft 5/2019

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Abstract

Social websites available over the Internet help users in predicting future events. User preferences over the web are in the form of blogs, textual content, public forum discussion and social media. However, reading informal discussions impact the users in the global market. In this paper we have proposed an SVM based classification method which assists the users to make informed transactions. Classifier makes use of the information available in the social media to make correct decision in the market. Our approach is compared with the traditional human based prediction approach and the results indicate that the classifier based prediction approach produces higher accuracy in terms of prediction compared to the traditional approach. Market window size is set to 30, 60 and 90 days respectively.

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Titel: Predicting user preferences on changing trends and innovations using SVM based sentiment analysis
verfasst von: K. Chidambarathanu
K. L. Shunmuganathan
Publikationsdatum: 15.12.2017
Verlag: Springer US
Erschienen in: Cluster Computing / Ausgabe Sonderheft 5/2019
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI: https://doi.org/10.1007/s10586-017-1505-0

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