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Latent Dirichlet Allocation in R
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this work references cited by second hop

References

  • 2010Speech and language processing3,546 cited
  • 1999Untangling text data mining883 cited
  • 2012The case for open computer programs537 cited
  • 2006Tapping the power of text mining433 cited
  • 2004Mapping knowledge domains383 cited

Cited by

  • 2016Citations, research topics and active countries in software engineering: A bibliometrics study114 cited
  • 2020The Effects of Green Restaurant Attributes on Customer Satisfaction Using the Structural Topic Model on Online Customer Reviews65 cited
  • 2018Finding Trends in Software Research39 cited
  • 2015Topics in the literature of transition economies and emerging markets32 cited
  • 2019Understanding Big Data Through a Systematic Literature Review: The ITMI Model29 cited
  • 2022Leveraging consumer behavior research to forge new insights into B2B buyer behavior: Contextualizing extant research and developing a research agenda26 cited
  • 2018Trace of Knowledge: Benchmarking Novel Text Mining Based Measurements18 cited
  • 2023Reading customers’ minds through textual big data: Challenges, practical guidelines, and proposals16 cited
  • 2018Tracing university–industry knowledge transfer through a text mining approach14 cited
  • 2014

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Finding Scientific Topics Revisited
7 cited
  • 2024Identifying the optimal number of topics in text mining: a case study on reindeer pastoralism literature4 cited
  • 2024Creating Metaclusters of Topics in Latent Dirichlet Allocation—Comparison of Bottom-Up and Top-Down Approach1 cited