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December 16, 2016Natural Language Engineering970 citationsOpen Access

Word2Vec

KCKenneth Church

Key Points

  • To evaluate the widespread adoption and high citation rate of Word2Vec using Thomas Kuhn's philosophical framework for emerging scientific paradigms.
  • Analyzed the Word2Vec algorithm's research trajectory against Kuhn's two core criteria for emerging scientific trends.
  • Evaluated the impact of releasing open-source code and data on community engagement and citation velocity.
  • Word2Vec satisfies Kuhn's criteria by delivering early promising results while leaving sufficient theoretical questions for subsequent researchers to explore.
  • Distributing public code and datasets significantly increases research velocity and downstream citation counts by lowering barriers for early adopters.

Abstract

Abstract My last column ended with some comments about Kuhn and word2vec. Word2vec has racked up plenty of citations because it satisifies both of Kuhn’s conditions for emerging trends: (1) a few initial (promising, if not convincing) successes that motivate early adopters (students) to do more, as well as (2) leaving plenty of room for early adopters to contribute and benefit by doing so. The fact that Google has so much to say on ‘How does word2vec work’ makes it clear that the definitive answer to that question has yet to be written. It also helps citation counts to distribute code and data to make it that much easier for the next generation to take advantage of the opportunities (and cite your work in the process).

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Cite This Study

Kenneth Church (2016) studied this question.

synapsesocial.com/papers/69d815e6b5518339b2ae2b33https://doi.org/10.1017/s1351324916000334
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