The article explains the significance of link prediction in social networks, focusing specifically on Twitch data to anticipate new follows between users. It elaborates on the methodical approach taken, including data importing, preprocessing, and formatting necessary for integration into a Neptune cluster. By converting raw dataset files containing user information and established friendships into a compatible CSV format for Neptune, the groundwork for efficient analysis and prediction is laid, enabling deeper exploration of potential new user connections.
Link prediction is crucial for anticipating social network connections, leveraging existing link structures and user features to enhance engagement through potential new follows.
The process begins with data preparation, where raw dataset files—representing Twitch users and friendships—must be converted into a format compatible with Neptune’s graph database.
Collection
[
|
...
]