A Text-Mining Research Based on LDA Topic Modelling: A Corpus-Based Analysis of Pakistan’s UN Assembly Speeches (1970–2018)

Autor: Sabahat Khan, Fasih Ahmed, Muhammad Mubeen
Rok vydání: 2022
Předmět:
Zdroj: International Journal of Humanities and Arts Computing. 16:214-229
ISSN: 1755-1706
1753-8548
DOI: 10.3366/ijhac.2022.0291
Popis: The UN General Assembly is a forum that conveys a country’s contributions or concerns. Pakistan, being a South Asian country, has echoed multiple concerns that have affected the peace process in Pakistan and South Asia. Hence, it is vital to understand the nature of these issues and the preferences raised at the General Assembly. The present research is underpinned by computational grounded theory, 1 which relies on the fact that meaning is hidden inside data. A total of nine topics emerged from the data. The results reveal that support for the war against terrorism, peace and security, terrorist attacks, the urging of the world community, diffusion of the nuclear threat, terrorism as a threat to prosperity, economic development, peace as an international challenge, and the Afghan peace process are the main issues concerning Pakistan. The analysis reveals that most of these relate to challenges linked to peace and security, economic problems and Afghan issues. The investigation concludes that the nation’s priority-setting is based on peace and security, economic development, and the Afghan peace process.
Databáze: OpenAIRE
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje