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Undersøgelse af Natural Language Processing til vurdering af online anmeldelser

Authors: Klindt, William Grynderup; Schmidt, Luchas Nickolaj; Nielsen, Jacob Peter Diesel;

Undersøgelse af Natural Language Processing til vurdering af online anmeldelser

Abstract

This study explores the use of Natural Language Processing as a tool for online reviews. By drawing on theories about machine learning, this article investigates how to develop a Natural Language Processing model in Python. The authors present two machine learning models which were developed through an iterative design process and by implementing various approaches from the TRIN-model. This study concludes that machine learning models like ours might not have a significant impact on the future of reviews, but we are optimistic about the potential of Natural Language Processing as a tool for categorizing specific aspects of a company’s services. This conclusion is based on the analysis and discussion of the results we gathered from our Natural Language Processing models.

Country
Denmark
Related Organizations
Keywords

Natural Language Processing

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    impulse
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  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Related to Research communities
Digital Humanities and Cultural Heritage
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