With the development of Web 2.0, social networks are becoming more popular. More and more scholars are working on big data analytics, hoping to find ways to exploit relevant business information in the huge data streams that are associated with online behavior. It is possible to retrieve social data, data from social media, from a variety of social networks, such as Twitter and Facebook. But how do you filter the signal from the noise?
With the use of social data it is possible to analyze, monitor and research how users behave on different social media platforms. In this project TwitterCounter and Social Honey work together to develop fully working end-to-end software to efficiently retrieve relevant information, the signal, from irrelevant social data, the noise.
The web based software named Social Signal Isolation Processing and Delivery (SS-IPD) focusses on the collection of huge amounts of accurate data without loss of accuracy and transforming this data in an abstract, universal way so that it can use input from any social media platform. SS-IPD uses a frequency detection filter based on work in the field of neuroscience for signal analysis. Using the filter, the value of the signal will be detected and this will give an output and contribute to high quality data management in social media marketing and online publishing. In this way this project contributes in the goals of the top sector HTSM and ICT and the main theme Data, data, data, action lines Innovative data management and Heterogeneous data, because the software helps to interpret large and heterogeneous data streams using novel data management techniques. Furthermore, the project makes a crossover with the top sector Creative Industry, where it can lead to business innovation and smart industry solutions in Media and ICT.