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</script>On this content, you will be provided with the source code of topic modeling using LDA. The datasets are coming from the crawling process that already done and being processed with LDA method to cluster the topics. After clustering the topics, there will be a graph that will show the number of each topic and the contribution of each document of the datasets.
Topic Modeling, LDA, Clustering
Topic Modeling, LDA, Clustering
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 3 |

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