An approach to analyze meta-data of web content sharing and tracking

The web and social media is an important platform for information sharing. A large amount of content is shared on various web sources such as websites, blogs, and social media platforms. The content can be re-shared on various social media platforms overtime, hence, the content spreads on different locations. In the result, it is hard to track the flow of content from the original source to all the possible re-shared locations. There are several cases where it is required to find the influencer who has participated most in content sharing. Some of these are; finding optimal ways to spread a specific type of content to large audience in less time, to drive social changes by targeting highly responsive audience, and to run social campaigns effectively.

Autorentext

Masters: Research in Computer & Systems Engineering. Institute: Technical University Ilmenau, Germany. Interests: Big Data, Data analytics, Complex event processing, web & mobile application development. Expertise: Web and mobile application development, Data analytics Apache Spark & Scala.