Affiliation:
1. Egypt Japan University of Science and Technology, Egypt and Faculty of Engineering, Alexandria University, Egypt
Abstract
In this work we analyze the lyrics of one of the most famous and influential Arab artists in the twentieth century, namely,
(Abdel ElHalim Hafez). Lyrics analysis provides a deep insight into the artist’s career evolution and his interactions with the surrounding environment including the social, political, and economic conditions. In order to perform such analysis we had to collect and compile the lyrics of Abdel ElHalim accompanied with the necessary metadata into an organized and structured form. The data are preprocessed by removing stop words and doing some normalization operations over the songs’ prose. We did not perform any lemmatization or stemming as the original form of the tokens convey much more information than the source words. We performed a lexical analysis in order to study both the lexical density and diversity over the course of Abdel ElHalim’s career life. We have as well studied the most significant words, idioms, and terms played in the songs using tools such as word clouds and more quantitative measures such as term frequency-inverse document frequency. We have divided the career life of Abdel ElHalim into sub-decades of length 5 years and all analyses are done both in a yearly fashion and more coarsely over such sub-decades. We have found a strong correlation between our statistical analysis and the socio-political status in Egypt and the Arab world during that time. This is especially relevant knowing that Abdel ElHalim is very much truly considered the son of the generation of the 1952 revolution in Egypt. The significance of Abdel ElHalim and his lyrics stem essentially from being contemporaneous to radical changes in Egypt across all sectors including political (support of liberation movements across the world, and the conflict with Israel), and socio-economic (especially changing the social class structure in Egypt). We also investigated the potential effectiveness of
PoS (Part of Speech)
tagging in genre analysis and classification.
Publisher
Association for Computing Machinery (ACM)
Cited by
2 articles.
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