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Making Sense of Qualitative Open-ended Reviews

by Nabanita Basu, Samir Kumar Bandyopadhyay
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 166 - Number 1
Year of Publication: 2017
Authors: Nabanita Basu, Samir Kumar Bandyopadhyay
10.5120/ijca2017913910

Nabanita Basu, Samir Kumar Bandyopadhyay . Making Sense of Qualitative Open-ended Reviews. International Journal of Computer Applications. 166, 1 ( May 2017), 38-40. DOI=10.5120/ijca2017913910

@article{ 10.5120/ijca2017913910,
author = { Nabanita Basu, Samir Kumar Bandyopadhyay },
title = { Making Sense of Qualitative Open-ended Reviews },
journal = { International Journal of Computer Applications },
issue_date = { May 2017 },
volume = { 166 },
number = { 1 },
month = { May },
year = { 2017 },
issn = { 0975-8887 },
pages = { 38-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume166/number1/27637-2017913910/ },
doi = { 10.5120/ijca2017913910 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:12:33.631803+05:30
%A Nabanita Basu
%A Samir Kumar Bandyopadhyay
%T Making Sense of Qualitative Open-ended Reviews
%J International Journal of Computer Applications
%@ 0975-8887
%V 166
%N 1
%P 38-40
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

While quantitative values can easily be compared, it is difficult to compare textual data. For an average end user it is often time-consuming and laborious to skim through thousands of open ended reviews put in place by other travellers/consumers. The algorithm proposed in this work is aimed to provide a quantitative summary of the thousands of reviews put forth by different individuals. The algorithm is aimed at determining the polarity (i.e. positivity, negativity and mixed/neutrality) of a review by searching for certain words and phrases that particularly refer to positive and negative emotions in an individual. The results obtained from the algorithm for traveller feedback is comparable to the cognitive ability of the average human mind. Use of the algorithm shall help towards saving time and work of an average human mind. The work presented is aimed at supporting an end user by providing him/her a quantitative positivity/negativity or neutrality summary across thousands of feedbacks/reviews put in place by other end users. Similar to comparing a value of 5 and 9 on a scale of 10, the algorithm outlined in this work shall help end users gauge and hence compare the degree of positivity or negativity associated with each user review.

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Index Terms

Computer Science
Information Sciences

Keywords

Sentiment analysis opinion mining opinion polarity cognitive ability

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