Extracting data from a large dataset of song titles and reviews towards malay songs / Nur Hajar Amirah Abd Aziz @ Abd Manaf, Nur Atikah Wan Mohamad Kamil and Nurul Afiqah Ramli

Abd Aziz @ Abd Manaf, Nur Hajar Amirah and Wan Mohamad Kamil, Nur Atikah and Ramli, Nurul Afiqah (2019) Extracting data from a large dataset of song titles and reviews towards malay songs / Nur Hajar Amirah Abd Aziz @ Abd Manaf, Nur Atikah Wan Mohamad Kamil and Nurul Afiqah Ramli. [Student Project] (Unpublished)

Abstract

Music is the written signs representing instrumental sound that produce beauty of form, harmony and expression of emotion. It is the act or art of singing burst into song. This study focused on analyzing Malay's song titles and reviews. The data was generated from the JOOX music player and Youtube channel. The objectives of this study are to identify the similar words used for song titles and reviews and to determine the relationship between words used for song titles and reviews. There are 250 songs have been collected in various genre with 609 reviews. The data is in a text form and being analyze by extracting word by word for each song's title and reviews. The most common word in Malay song titles and reviews are determine by using tibble function in R programming and presented in cloud form. The relationship among words in song's reviews are measured using Pairwise correlation coefficient. The Malay songs titles are also presented via visualization of a network of bigrams. The analysis of results found that the most common word used for Malay songs titles is ''cinta ". While the most common word used for Malay songs reviews is song. The relationship among the words in song reviews are statistically significant with positive relationship between sad and you, sad and all, songs and singer, deep and you, deep and sad, and deep and all. 'cinta' is a common center of node. which is often followed by the song title.

Metadata

Item Type: Student Project
Creators:
Creators
Email / ID Num.
Abd Aziz @ Abd Manaf, Nur Hajar Amirah
UNSPECIFIED
Wan Mohamad Kamil, Nur Atikah
UNSPECIFIED
Ramli, Nurul Afiqah
UNSPECIFIED
Contributors:
Contribution
Name
Email / ID Num.
Thesis advisor
Khairul Azmi, Nurul Nisa’
UNSPECIFIED
Subjects: Q Science > QA Mathematics > Mathematical statistics. Probabilities
Q Science > QA Mathematics > Mathematical statistics. Probabilities > Data processing
Q Science > QA Mathematics > Analysis
Q Science > QA Mathematics > Analysis > Analytical methods used in the solution of physical problems
Divisions: Universiti Teknologi MARA, Negeri Sembilan > Seremban Campus > Faculty of Computer and Mathematical Sciences
Programme: Bachelor of Science (Hons.) Statistics
Keywords: Extracting data, large dataset, song titles, reviews, malay songs
Date: 2019
URI: https://ir.uitm.edu.my/id/eprint/50158
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