A Text-Mining Research Based on LDA Topic Modelling: A Corpus-Based Analysis of Pakistan's UN Assembly Speeches (1970–2018). Issue 2 (September 2022)

• Record Type: Journal Article
• Authors: Khan, Sabahat; Ahmed, Fasih; Mubeen, Muhammad
• Is Part Of: International journal of humanities and arts computing. Volume 16:Issue 2(2022)
• Page Start: 214
• Page End: 229
• Publication Date: 2022-09
• Subjects: topic modelling -- natural language processing -- computational grounded theory -- data-driven approach -- UN General Assembly Debate; Humanities -- Data processing -- Periodicals; Arts -- Data processing -- Periodicals; 001.30285
• DOI: 10.3366/ijhac.2022.0291
• Languages: English
• ISSNs: 1753-8548

Abstract

Abstract : 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.