Topic Modeling of the Pakistani Economy in English Newspapers via Latent Dirichlet Allocation (LDA)

被引:7
|
作者
Ahmed, Fasih [1 ]
Nawaz, Muhammad [1 ]
Jadoon, Aisha [1 ]
机构
[1] COMSATS Univ, Dept Humanities, Islamabad, Pakistan
来源
SAGE OPEN | 2022年 / 12卷 / 01期
关键词
topic modeling; natural language processing; grounded theory; data-driven approach; TERRORISM; GROWTH; ENERGY; IMPACT; NEWS;
D O I
10.1177/21582440221079931
中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
This research paper explores aspects of the Pakistani economy using the Latent Dirichlet Allocation (LDA) technique. The data based on 3,000 articles were collected from two Pakistani English newspapers, Dawn and The News, (2015-2020), through Lexis Nexis database. The headlines of the news articles relevant to Pakistan's economy, were taken into account. By employing the data-driven approach of the grounded theory, it is found that changes in policies, security preference, textile industry, the shift of energy, inflation, growth and investment, mega projects, sustainable democracy and poverty control need to be focused to overcome the challenges of Pakistan's economy. It also reveals that mega projects like the China Pakistan Economic Corridor (CPEC) are called to boost Pakistan's economy. The results show that smooth trading would help reduce poverty in the country.
引用
收藏
页数:9
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