2019 IEEE International Conference on Big Data (Big Data) 2019
DOI: 10.1109/bigdata47090.2019.9006160
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Search for K: Assessing Five Topic-Modeling Approaches to 120,000 Canadian Articles

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Cited by 3 publications
(2 citation statements)
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“…PMI is the probability of a pair of topic words with logarithmic calculation. Equation ( 2) denotes the NPMI calculation, where P (x, y) represents the probability of token x and token y occuring in the documents, is a smoothing constant and a "higher γ gives a higher NPMI more weight" [30]. The positive value of NPMI coherence means that the topic is relevant to the document.…”
Section: A Metricsmentioning
confidence: 99%
“…PMI is the probability of a pair of topic words with logarithmic calculation. Equation ( 2) denotes the NPMI calculation, where P (x, y) represents the probability of token x and token y occuring in the documents, is a smoothing constant and a "higher γ gives a higher NPMI more weight" [30]. The positive value of NPMI coherence means that the topic is relevant to the document.…”
Section: A Metricsmentioning
confidence: 99%
“…Yet, computational social science has not been well informed by an explosion in methods and algorithms for topic modeling in the past two decades [1], [5], [6]. As suggested by DiMaggio [7], most topic-modeling techniques require various methodological decisions that many social scientists are unfamiliar with, have not considered, or lack experience with.…”
Section: Introductionmentioning
confidence: 99%