Opinion Mining from Online Travel Reviews: An Exploratory Investigation on Pakistan Major Online Travel Services Using Natural Language Processing
Online tourism evaluations are a valuable origin of data for traveler organizations, defining as they could be excellently recognized critically prompting traveler opinion-designing using opinion mining. As technology advanced, online review forums of any organization become an attractive source of...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10077573/ |
| _version_ | 1797855314583748608 |
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| author | Bushra Kanwal Saif Ur Rehman Azhar Imran Rana Saud Shaukat Jianqiang Li Abdulkareem Alzahrani Ans D. Alghamdi Fawaz Khaled Alarfaj |
| author_facet | Bushra Kanwal Saif Ur Rehman Azhar Imran Rana Saud Shaukat Jianqiang Li Abdulkareem Alzahrani Ans D. Alghamdi Fawaz Khaled Alarfaj |
| author_sort | Bushra Kanwal |
| collection | DOAJ |
| description | Online tourism evaluations are a valuable origin of data for traveler organizations, defining as they could be excellently recognized critically prompting traveler opinion-designing using opinion mining. As technology advanced, online review forums of any organization become an attractive source of communication with them, where people can share their views in the form of comments. The main determination of this research article is to recognize normal topics and connect them to contrasts in web-based travel reviews. Online millions of reviews, got from two significant web-based travel organizations (Uber, and Careem) in Pakistan, and a semantic affiliation examination was utilized to extract thematic words and construct a semantic affiliation organization. In the Python programming language, we use natural language processing (NLP), which includes data cleansing and tokenization. The results of network visualization are able to evidently recognize main topics and thematic words with social network associations. The proposed logical system extends our grip on the strategic complications and gives new points of view on the best way to dig popular assessments to assist vacationers, inns, and travel industry organizations. |
| first_indexed | 2024-04-09T20:21:42Z |
| format | Article |
| id | doaj.art-22dde7ecc3e3431e9b2bf6696e351b04 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-09T20:21:42Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-22dde7ecc3e3431e9b2bf6696e351b042023-03-30T23:01:06ZengIEEEIEEE Access2169-35362023-01-0111299342994510.1109/ACCESS.2023.326011410077573Opinion Mining from Online Travel Reviews: An Exploratory Investigation on Pakistan Major Online Travel Services Using Natural Language ProcessingBushra Kanwal0Saif Ur Rehman1https://orcid.org/0000-0002-5810-6479Azhar Imran2https://orcid.org/0000-0003-3598-2780Rana Saud Shaukat3Jianqiang Li4https://orcid.org/0000-0003-1995-9249Abdulkareem Alzahrani5https://orcid.org/0000-0003-3658-1284Ans D. Alghamdi6https://orcid.org/0000-0002-7583-6086Fawaz Khaled Alarfaj7School of Software Engineering, Beijing University of Technology, Beijing, ChinaUniversity Institute of Information Technology (UIIT), Arid Agriculture University, Rawalpindi, PakistanDepartment of Creative Technologies, Faculty of Computing and AI, Islamabad, PakistanUniversity Institute of Information Technology (UIIT), Arid Agriculture University, Rawalpindi, PakistanSchool of Software Engineering, Beijing University of Technology, Beijing, ChinaFaculty of Computer Science and Information Technology, Al Baha University, Al Baha, Saudi ArabiaFaculty of Computer Science and Information Technology, Al Baha University, Al Baha, Saudi ArabiaCollege of Computer Sciences and Information Technology, King Faisal University, Al-Ahsa, Saudi ArabiaOnline tourism evaluations are a valuable origin of data for traveler organizations, defining as they could be excellently recognized critically prompting traveler opinion-designing using opinion mining. As technology advanced, online review forums of any organization become an attractive source of communication with them, where people can share their views in the form of comments. The main determination of this research article is to recognize normal topics and connect them to contrasts in web-based travel reviews. Online millions of reviews, got from two significant web-based travel organizations (Uber, and Careem) in Pakistan, and a semantic affiliation examination was utilized to extract thematic words and construct a semantic affiliation organization. In the Python programming language, we use natural language processing (NLP), which includes data cleansing and tokenization. The results of network visualization are able to evidently recognize main topics and thematic words with social network associations. The proposed logical system extends our grip on the strategic complications and gives new points of view on the best way to dig popular assessments to assist vacationers, inns, and travel industry organizations.https://ieeexplore.ieee.org/document/10077573/Opinion miningonline travel reviewssocial network associationthematic wordsnatural language processingsentiment analysis |
| spellingShingle | Bushra Kanwal Saif Ur Rehman Azhar Imran Rana Saud Shaukat Jianqiang Li Abdulkareem Alzahrani Ans D. Alghamdi Fawaz Khaled Alarfaj Opinion Mining from Online Travel Reviews: An Exploratory Investigation on Pakistan Major Online Travel Services Using Natural Language Processing IEEE Access Opinion mining online travel reviews social network association thematic words natural language processing sentiment analysis |
| title | Opinion Mining from Online Travel Reviews: An Exploratory Investigation on Pakistan Major Online Travel Services Using Natural Language Processing |
| title_full | Opinion Mining from Online Travel Reviews: An Exploratory Investigation on Pakistan Major Online Travel Services Using Natural Language Processing |
| title_fullStr | Opinion Mining from Online Travel Reviews: An Exploratory Investigation on Pakistan Major Online Travel Services Using Natural Language Processing |
| title_full_unstemmed | Opinion Mining from Online Travel Reviews: An Exploratory Investigation on Pakistan Major Online Travel Services Using Natural Language Processing |
| title_short | Opinion Mining from Online Travel Reviews: An Exploratory Investigation on Pakistan Major Online Travel Services Using Natural Language Processing |
| title_sort | opinion mining from online travel reviews an exploratory investigation on pakistan major online travel services using natural language processing |
| topic | Opinion mining online travel reviews social network association thematic words natural language processing sentiment analysis |
| url | https://ieeexplore.ieee.org/document/10077573/ |
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