Big Data Analytics and Fuzzy Technology: Extracting Information from Social Data

Abstract

Data becomes overwhelming present in almost all aspects of manufacturing, finance, commerce and entertainment. Today’s world seems to generate tons of data related to all aspect of human activities every minute. A lot of hope and expectations are linked to benefits that analysis of such data could bring. Among many sources of data, social networks start to play a very important role. Indications what individuals think about almost anything related to their lives, what they like and dislike are embedded in posts and notes they leave on the social media platforms. Therefore, discovering the users’ opinions and needs is very critical for industries as well as governments. Analysis of such data—recognized as a big data due to its tremendous size—is of critical importance. The theory of fuzzy sets and systems, introduced in 1965, provides the researchers with techniques that are able to cope with imprecise information expressed linguistically. This theory constitutes a basis for designing and developing methodologies of processing data that are able to identify and understand views and judgments expressed in a unique, human way—the core of information generated by the users of social networks. The paper tries to recognize a few important example of extracting value from social network data. Attention is put on application of fuzzy set and systems based methodologies in processing such data.