Detection of Topics and Construction of Search Rules on Twitter

This study proposes an improvement to the Insight Centre for Data Analytics algorithm, which identifies the most relevant topics in a corpus of tweets, and allows the construction of search rules for that topic or topics, in order to build a corpus of tweets for analysis. The improvement shows above 14% improvement in Purity and other metrics, and an execution time of 10% compared to Latent Dirichlet Allocation (LDA).

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