@thesis{NunezFranco2023, author = {Nu{\~n}ez Franco, Luis Fernando}, title = {On sentiment analysis of Twitter content related to the FIFA World CUP 2022 in Qatar}, publisher = {Technische Hochschule Ingolstadt}, address = {Ingolstadt}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:573-33627}, pages = {ii, 63}, school = {Technische Hochschule Ingolstadt}, year = {2023}, abstract = {The decision to award the 2022 World Cup to Qatar has been met with widespread controversy, criticism, and opposition from fans and the football community. There have been numerous allegations of bribery and corruption within FIFA, as well as reports of human rights abuses, including poor conditions for migrant workers, restrictions on women's rights, and discrimination against the LGBTQ+ community. Furthermore, the intense heat in Qatar and the decision to move the tournament to a different time of year has had significant financial impacts on professional football leagues and related businesses. Public opinion has become strongly polarized due to these issues, which is why in this thesis, a pre-trained model using Python programming language is utilized to analyze the Twitter sentiment towards the 2022 football World Cup.}, language = {en} }