Total for the last 12 months
number of access : ?
number of downloads : ?
ID 116410
Author
Kamata, Suzanne Naruto University of Education
Keywords
natural language processing (NLP)
Python
analysis of questionnaire responses in text format
text analysis
reading-while-listening
Listening-only
Content Type
Journal Article
Description
The main purpose of the research reported here is to show that the questionnaire responses in text format can be processed and statistically analyzed to some extent by computer programs. We employ unigram, bigram and trigram frequency calculations with the assistance of Python programming in order to analyze the questionnaire responses in text format.
Questionnaire responses chosen from options can be easily statistically analyzed whether they are on a ratio, interval, ordered or nominal scale. In contrast, descriptive questionnaire responses have long been read and interpreted by researchers themselves. They have been analyzed by human labor alone. This could to some extent lead to arbitrary and subjective interpretations and analyses. We demonstrate in this paper that natural language processing techniques in Python could help analyze questionnaire responses in text format more objectively and accurately.
Journal Title
Hyperion
ISSN
18840515
NCID
AN00040454
Publisher
徳島大学英語英文学会
Volume
67
Start Page
1
End Page
13
Sort Key
1
Published Date
2021-03-31
EDB ID
FullText File
language
eng
TextVersion
Publisher
departments
Integrated Arts and Sciences