Sentiment Dynamics in Social Media News Channels
This study addresses the problem of understanding sentiment dynamics in social media news for media analysts and platforms, but it is incremental as it applies existing methods to new data.
The paper analyzed how news channels use sentiment to attract users on social media, comparing television, radio, and print media, and found that user opinion sentiment strongly correlates with news post sentiment and source type, based on a dataset of 0.15 million posts and 1.13 billion reactions.
Social media is currently one of the most important means of news communication. Since people are consuming a large fraction of their daily news through social media, most of the traditional news channels are using social media to catch the attention of users. Each news channel has its own strategies to attract more users. In this paper, we analyze how the news channels use sentiment to garner users' attention in social media. We compare the sentiment of social media news posts of television, radio and print media, to show the differences in the ways these channels cover the news. We also analyze users' reactions and opinion sentiment on news posts with different sentiments. We perform our experiments on a dataset extracted from Facebook Pages of five popular news channels. Our dataset contains 0.15 million news posts and 1.13 billion users reactions. The results of our experiments show that the sentiment of user opinion has a strong correlation with the sentiment of the news post and the type of information source. Our study also illustrates the differences among the social media news channels of different types of news sources.