• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Phrase-based Topic and Sentiment Detection and Tracking Model using Incremental HDP

Vol. 11, No.12, December 31, 2017
10.3837/tiis.2017.12.012, Download Paper (Free):

Abstract

Sentiments can profoundly affect individual behavior as well as decision-making. Confronted with the ever-increasing amount of review information available online, it is desirable to provide an effective sentiment model to both detect and organize the available information to improve understanding, and to present the information in a more constructive way for consumers. This study developed a unified phrase-based topic and sentiment detection model, combined with a tracking model using incremental hierarchical dirichlet allocation (PTSM_IHDP). This model was proposed to discover the evolutionary trend of topic-based sentiments from online reviews. PTSM_IHDP model firstly assumed that each review document has been composed by a series of independent phrases, which can be represented as both topic information and sentiment information. PTSM_IHDP model secondly depended on an improved time-dependency non-parametric Bayesian model, integrating incremental hierarchical dirichlet allocation, to estimate the optimal number of topics by incrementally building an up-to-date model. To evaluate the effectiveness of our model, we tested our model on a collected dataset, and compared the result with the predictions of traditional models. The results demonstrate the effectiveness and advantages of our model compared to several state-of-the-art methods.


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Cite this article

[IEEE Style]
YongHeng Chen, YaoJin Lin and WanLi Zuo, "Phrase-based Topic and Sentiment Detection and Tracking Model using Incremental HDP," KSII Transactions on Internet and Information Systems, vol. 11, no. 12, pp. 5905-5926, 2017. DOI: 10.3837/tiis.2017.12.012

[ACM Style]
Chen, Y., Lin, Y., and Zuo, W. 2017. Phrase-based Topic and Sentiment Detection and Tracking Model using Incremental HDP. KSII Transactions on Internet and Information Systems, 11, 12, (2017), 5905-5926. DOI: 10.3837/tiis.2017.12.012