Sentiment and growth of different news categories on Twitter : A study in Natural Language Processing
Abstract: In this age of digitalization, people have begun to change their news consumption behavior. More than half the population of the world has internet access and thereby readily available platforms for acquiring and disseminating news. Twitter has evolved into being a staple for news discussions and even transforming into a stable news source provider. This study aims to examine Twitter as a legitimate news media based on certain news categories and how they differ regarding public interest and opinion. The categories are celebrity, crime, economy, politics & global and we examined the relative growth rate and public sentiment for each category during a period of 10 hours before and 14 hours after an event occurring. The results indicate that the political news category had the most public appraise and also the highest public interest. Furthermore, the political news category also had the lowest fluctuation regarding public sentiment. On the other side of the spectrum, the crime category had both the most negative public sentiment and the lowest relative growth rate.
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