Social big data applications and challenges

Abstract

Lifestyles of individuals have changed drastically in the last two decades with the impact of social media platforms which transforms individuals from being users into an asset of social media. The assets now become very precious and seriously attract who can generate useful or harmful values. In this context, studies conducted in the last 5 years are analyzed based on the methodology covering implementation areas, data sources, data size, methods and tools. The studies were classified and summarized under nine main "research fields," and a "purpose-based" classification under three main purposes was investigated. The results have shown that even if data obtained from social media platforms are often preferred in the studies, issues such as compliance with legal regulations, data processing, confidentiality and privacy of data also bring difficulties; collection and processing of social big data are a serious obstacle to the realization of many studies; not enough data sources provided by public or private enterprises; most of the studies carried out on text data, and the rest focused on location and image data; mostly machine learning methods are preferred in applications. This study differs from previous literature reviews by revealing comprehensively how social big data can be transformed into practice with a holistic perspective.