Abstract
The popularity of social media and computer-mediated communication has resulted in high-volume and highly semantic data about digital social interactions. This constantly accumulating data has been termed as Big Social Data or Social Big Data, and various visions about how to utilize that have been presented. However, as relatively new concepts, there are no solid and commonly agreed definitions of them. We argue that the emerging research field around these concepts would benefit from understanding about the very substance of the concept and the different viewpoints to it. With our review of earlier research, we highlight various perspectives to this multi-disciplinary field and point out conceptual gaps, the diversity of perspectives and lack of consensus in what Big Social Data means. Based on detailed analysis of related work and earlier conceptualizations, we propose a synthesized definition of the term, as well as outline the types of data that Big Social Data covers. With this, we aim to foster future research activities around this intriguing, yet untapped type of Big Data.
Highlights
We live in an “always-on society” [1,2,3], meaning that people constantly interact with each other
Our synthesis and definition of Big Social Data Drawing from our overview of the related literature and observation of contributing science fields we provide a meta-level definition of the synthesized BSD concept as follows: Big Social Data is any high-volume, high-velocity, high-variety and/or highly semantic data that is generated from technology-mediated social interactions and actions in digital realm, and which can be collected and analyzed to model social interactions and behavior
Our literature overview shows that majority of related work on BSD is focused on the analysis of social data, giving less attention to describing what BSD is
Summary
Background We live in an “always-on society” [1,2,3], meaning that people constantly interact with each other. An average Internet user consumes and shares large amounts of digital content every day through popular social online services, such as Facebook, Twitter, YouTube, Instagram and SnapChat From data perspective, this has led to emergence of extensive amounts of human-generated data [4, 5] with diverse social uses and rich meanings (for example, communication text, videos for entertainment and self-representation, sharing of news and other 3rd party content in social media). This has led to emergence of extensive amounts of human-generated data [4, 5] with diverse social uses and rich meanings (for example, communication text, videos for entertainment and self-representation, sharing of news and other 3rd party content in social media) Such unstructured/semi-structured, yet semantically rich data has been argued to constitute 95% of all Big Data [6]. This Social Data explosion has resulted in theorizations and studies about the emerging topic of Big Social Data (BSD)
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