Global News Engagement On Social Media

This comprehensive dataset offers a deep dive into the social media engagement metrics of nearly 4,000 posts from four of the world's leading news channels: CNN, BBC, Al Jazeera, and Reuters. Curated to provide a holistic view of global news interaction on social media, the collection stands out for its meticulous assembly and broad spectrum of content.

Dataset Overview:
Spanning various global events, topics, and narratives, this dataset is a snapshot of how news is consumed and interacted with on social media platforms. It serves as a rich resource for analyzing trends, engagement patterns, and the dissemination of information across international borders.

Data Science Applications:
Ideal for researchers and enthusiasts in the fields of data science, media studies, and social analytics, this dataset opens doors to numerous explorations such as engagement analysis, trend forecasting, content strategy optimization, and the study of information flow in digital spaces. It also holds potential for machine learning projects aiming to predict engagement or classify content based on interaction metrics.

Column Descriptors:
Each record in the dataset is detailed with the following columns:

• text: The title or main content of the post.
• likes: The number of likes each post has garnered.
• comments: The number of comments left by viewers.
• shares: How many times the post has been shared.

Ethically Mined Data:
The collection of this dataset was conducted with the highest ethical standards in mind, ensuring compliance with data privacy laws and platform policies. By anonymizing data where necessary and focusing solely on publicly available information, it respects both individual privacy and intellectual property rights.

Special thanks are extended to the Facebook platform and the respective news channels for their openness and the rich public data they provide. This dataset not only celebrates the vibrant exchange on social media but also underscores the importance of responsible data use and sharing in fostering understanding and innovation.