Data scraping to analyze tourist attractions in Malaysia / Muhammad Aslam Md Adam
In Malaysia, there is a lot of interesting places to visit especially for the foreign traveler. Usually, before start traveling, people always plan and looking for information about the place that they want to visit. With the Internet, every information can be easily obtained. There are many website...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2019
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/24994/1/TD_MUHAMMAD%20ASLAM%20BIN%20MD%20ADAM%20CS%2019_5.pdf |
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| Summary: | In Malaysia, there is a lot of interesting places to visit especially for the foreign traveler. Usually, before start traveling, people always plan and looking for information about the place that they want to visit. With the Internet, every information can be easily obtained. There are many websites that provide information about popular places that can be visited. However, not all websites are updated, with some of them are lastly updated in years ago, and some of them do not provide a review section. This can lead to information inaccuracy and is questionable to the people who are desired to visit the place. It also causes a problem to the initial plan and it takes a lot of time to search through the internet to find good information about the location. By using the information about the attraction place that has been posted on social media such as Twitter, this application will extract the data, analyze the information and display the information to the end user to help the user in making decision, planning and getting a good understanding about the places. Sentiment analysis also has been conducted by this application in order to give a quick review and reliable information to the end user. In this project, R programming language is used since R language is one of the programming languages that are suitable in producing and conducting analysis, where it has multiple functions and packages that can be used to make the analysis easier. Twitter API allows the data to be extract and the R language help in processing those data which give a good analysis result about the place of attraction in the type of web application. |
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