Topic Modeling with Xxxxxx Sample Clauses

Topic Modeling with Xxxxxx. When there are a considerable volume of texts, Topic Modeling is often employed to generate word clustering that represents hidden topics. Although computer scientists nowadays rarely use Gensim and Mallet, these Topic Mod- eling algorithms still maintain popular in social science studies [9, 10]. Gensim utilizes Variational Bayes sampling method which yields an advantageous processing speed, whereas Mallet uses Xxxxx Sampling, which has a higher precision than Gensim [13]. Since this research needs to process a dataset of more than one million tweets, between the trade off between processing time and precision, the former is more essential. In addition, Xxxxxx provides an interactive visualization that presents how the extracted topics overlap, the words summarizing each topic, and the proportion of the topic. To improve the efficiency of Topic Modeling which performs better when there are as many separate files as possible, each tweet is stored as a single file. For instance, we have 85,862 tweets for March 4th, and thus we will have 85,862 files for Topic Modeling. Gensim will be applied to each dataframe for extracting topic clustering.
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