A framework for identifying influential people by analyzing social media data

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. In this paper, we introduce a new framework for identifying the most influential people from social sensor networks. Selecting influential people from social networks is a complicated task as it depends on many metrics like the network of friends, followers, reactions, comments, shares, etc. (e.g., friends-of-a-friend, friends-of-a-friend-of-a-friend). Data on social media are increasing day-by-day at an enormous rate. It is also a challenge to store and process these data. Towards this goal, we use Hadoop to store data and Apache Spark for the fast computation of the data. To select influential people, we apply the mechanisms of skyline query and top-k query. To the best of our knowledge, this is the first work to apply the Apache Spark framework to identify influential people on social sensor network, such as online social media. Our proposed mechanism can find influential people very quickly and efficiently on the data pattern of Facebook.