2020
DOI: 10.1017/9781108684163
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Mining of Massive Datasets

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Cited by 413 publications
(410 citation statements)
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“…Results obtained from the synopsis data (Panel B) yield the same conclusion. This finding is supported by further results presented in Appendix, which rely on a more sophisticated natural-language processing technique, "Term Frequency-Inverse Document Frequency" (TF-IDF), which gives more weight to words that are more frequent in a particular document, and less weight to those are more frequent in the entire collection of texts in the sample (Leskovec et al, 2014). Thus, we conclude that the policy change did not alter the nature of storylines developed by films targeting the Chinese market.…”
Section: Unobservable Characteristicssupporting
confidence: 53%
“…Results obtained from the synopsis data (Panel B) yield the same conclusion. This finding is supported by further results presented in Appendix, which rely on a more sophisticated natural-language processing technique, "Term Frequency-Inverse Document Frequency" (TF-IDF), which gives more weight to words that are more frequent in a particular document, and less weight to those are more frequent in the entire collection of texts in the sample (Leskovec et al, 2014). Thus, we conclude that the policy change did not alter the nature of storylines developed by films targeting the Chinese market.…”
Section: Unobservable Characteristicssupporting
confidence: 53%
“…(vi) Steps (iii) to (v) are repeated until all of the nodes in G α and G β are traversed. The real-world datasets contain eight networks downloaded from the websites Stanford Large Network Dataset Collection [74], Link Prediction Group [75], and Network Analysis of Advogato [76]. In a real scenario, OSN application users are often wary of their privacy.…”
Section: Methodsmentioning
confidence: 99%
“…Definition 4 Jaccard similarity Given a network G = (V, E, A), for any pair of nodes V i , V j ∈ V, the Jaccard similarity between nodes V i and V j with respect to attribute is indicated as J(A i , A j ) and is defined as the size of the intersection divided by the size union of the data sets, as given below [44]:…”
Section: Attribute Similarity Metricmentioning
confidence: 99%