Investigation of social media users sentiments about money laundering
DOI:
https://doi.org/10.3846/bm.2025.1449Keywords:
social networks, money laundering, opinions, sentiment analysis, algorithmic content processingAbstract
This study aims to analyse how user’s opinions on money laundering are shaped on social networking platforms, based on indicators of content, emotional polarity and user behaviour. The object of the study is the attitudes of social media users towards money laundering and the main objective is to empirically assess the impact of the content of these platforms on public perceptions of money laundering practices. The theoretical part discusses the approaches to the functioning of social networks and the prevention of money laundering, while the empirical part conducts sentiment analysis and content processing using social network API data.
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This work is licensed under a Creative Commons Attribution 4.0 International License.