andrew_gelman_stats andrew_gelman_stats-2013 andrew_gelman_stats-2013-2103 knowledge-graph by maker-knowledge-mining

2103 andrew gelman stats-2013-11-16-Objects of the class “Objects of the class”


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Introduction: Objects of the class “Foghorn Leghorn” : parodies that are more famous than the original. (“It would be as if everybody were familiar with Duchamp’s Mona-Lisa-with-a-moustache while never having heard of Leonardo’s version.”) Objects of the class “Whoopi Goldberg” : actors who are undeniably talented but are almost always in bad movies, or at least movies that aren’t worthy of their talent. (The opposite: William Holden.) Objects of the class “Weekend at Bernie’s” : low-quality movie, nobody’s actually seen it, but everybody knows what it’s about. (Other examples: Heathers and Zelig.) I love these. We need some more.


Summary: the most important sentenses genereted by tfidf model

sentIndex sentText sentNum sentScore

1 Objects of the class “Foghorn Leghorn” : parodies that are more famous than the original. [sent-1, score-0.387]

2 (“It would be as if everybody were familiar with Duchamp’s Mona-Lisa-with-a-moustache while never having heard of Leonardo’s version. [sent-2, score-0.556]

3 ”) Objects of the class “Whoopi Goldberg” : actors who are undeniably talented but are almost always in bad movies, or at least movies that aren’t worthy of their talent. [sent-3, score-1.715]

4 ) Objects of the class “Weekend at Bernie’s” : low-quality movie, nobody’s actually seen it, but everybody knows what it’s about. [sent-5, score-0.764]


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tfidf for this blog:

wordName wordTfidf (topN-words)

[('objects', 0.499), ('movies', 0.352), ('class', 0.274), ('duchamp', 0.246), ('undeniably', 0.246), ('everybody', 0.237), ('goldberg', 0.214), ('talented', 0.19), ('actors', 0.187), ('weekend', 0.187), ('worthy', 0.176), ('william', 0.157), ('movie', 0.145), ('opposite', 0.123), ('familiar', 0.121), ('famous', 0.113), ('knows', 0.112), ('nobody', 0.11), ('heard', 0.104), ('aren', 0.102), ('love', 0.1), ('seen', 0.087), ('almost', 0.086), ('examples', 0.084), ('bad', 0.073), ('least', 0.067), ('never', 0.067), ('always', 0.064), ('need', 0.062), ('actually', 0.054), ('would', 0.027)]

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