Topic Modeling on Online News.Portal Using Latent Dirichlet Allocation (LDA)

https://doi.org/10.22146/ijccs.74383

Mohammad Rezza Fahlevvi(1*), Azhari SN(2)

(1) Master Program of Computer Science, FMIPA UGM, Yogyakarta
(2) Department of Computer Science and Electronics, FMIPA UGM, Yogyakarta
(*) Corresponding Author

Abstract


The amount of News displayed on online news portals. Often does not indicate the topic being discussed, but the News can be read and analyzed. You can find the main issues and trends in the News being discussed. It would be best if you had a quick and efficient way to find trending topics in the News. One of the methods that can be used to solve this problem is topic modeling.

Theme modeling is necessary to allow users to easily and quickly understand modern themes' development. One of the algorithms in topic modeling is the Latent Dirichlet Allocation (LDA). This research stage begins with data collection, preprocessing, n-gram formation, dictionary representation, weighting, topic model validation, topic model formation, and topic modeling results.

            Based on the results of the topic evaluation, the. The best value of topic modeling using coherence was related to the number of passes. The number of topics produced 20 keys, five cases with a 0.53 coherence value. It can be said to be relatively stable based on the standard coherence value.

Keywords


News Portal; Topic Modelling; Latent Dirichlet Allocation; Coherence Value

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References

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DOI: https://doi.org/10.22146/ijccs.74383

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