Data Science in Social Network Applications: Presentations
Social networks are a huge platform for sharing knowledge and keeping in touch. The main component in social networks which drives the engagement is the connections being made everyday. In this analysis, we are going to talk about the effect of a member's network structure on how member interacts with different products. We analyze the effect of structural diversity in members network on their engagement level with a social network.
Reddit is usually referred as the front page of the Internet since it is a dominant force in reaching the most recent content on the web. Reddit is organized as a collection of sub-communities, so-called subreddits. In this presentation we are interested in two main questions: Can one characterize the relationships between subreddits? Secondly, given a list of subreddits that a user has posted in, can we recommend relevant subreddits?
A/B testing is widely used among online websites, including social network sites such as Facebook, LinkedIn, and Twitter to make data-driven decisions. General A/B testing frameworks and methodologies have been discussed extensively in several previous work [1, 2, 3, 4]. In this work, we focus on the challenges that arise particularly when running A/B tests at large scale in a social network setting, and how we address them at LinkedIn.