Social media analytics in distributed environment

OData support
Supervisor:
Gincsai Gábor
Department of Automation and Applied Informatics

Twitter is one of the most popular social networks, people can

easily share content with others. This method of content sharing can be very

efficient, albeit it heavily depends on the time of the publishing.

My software addresses this problem by analysing the behavior of our follower

base. After this step, the application tells us when should we publish our

content to maximize the number of impressions.

My chosen platform was Node.JS, because it is designed for these kind of

applications. It scales well, one can write distributed network applications

very easily.

The JavaScript language is very popular, it supports various programming

paradigms (object-oriented, functional, etc.), its performance is very

impressive, it is comparable to native languages like C++, Java, C\#,

and it improves continuously.

My top priority during the development was that the individual software

components should be loosely coupled and lightweight. These properties

are necessary for a scalable, distributed system.

Downloads

Please sign in to download the files of this thesis.