Decoding customer experiences in rail transport service: application of hybrid sentiment analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3ANPJTYMC4" target="_blank" >RIV/00216208:11320/23:NPJTYMC4 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/10.1007/s12469-021-00289-7" target="_blank" >https://link.springer.com/10.1007/s12469-021-00289-7</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s12469-021-00289-7" target="_blank" >10.1007/s12469-021-00289-7</a>
Alternative languages
Result language
angličtina
Original language name
Decoding customer experiences in rail transport service: application of hybrid sentiment analysis
Original language description
"The paper aims to enhance customers’ satisfaction levels by identifying improvements in the service quality of the rail transport industry in developing countries such as India. A multi-algorithmic combination of a LEXICON analysis and a Naïve Bayes machine learning hybrid approach to sentiment analysis is performed for identifying passengers’ opinions on the services provided by Indian Railways."
Czech name
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Czech description
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Classification
Type
J<sub>ost</sub> - Miscellaneous article in a specialist periodical
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
"Public Transport"
ISSN
1866-749X
e-ISSN
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Volume of the periodical
15
Issue of the periodical within the volume
1
Country of publishing house
US - UNITED STATES
Number of pages
30
Pages from-to
31-60
UT code for WoS article
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EID of the result in the Scopus database
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