Social Media Data in Research: Provenance Challenges

Abstract

Abstract. In this paper we argue that understanding the provenance of social media datasets and their analysis is critical to addressing challenges faced by the social science research community in terms of the reliability and reproducibility of research utilising such data. Based on analysis of existing projects that use social media data, we present a number of research questions for the provenance community, which if addressed would help increase the transparency of the research process, aid reproducibility, and facilitate data reuse in the social sciences.

Big social data provenance framework for Zero-Information Loss Key-Value Pair (KVP) Database

“…volume, velocity, and variety, where volume means rapidly growing social data, velocity is related to the dissemination of information with tremendous speed, and variety refers to diverse formats of social data. Nowadays, the volume, velocity, and variety of Big Social Data are facing the challenges of capturing provenance [12] and evaluating trustworthiness of social data [29]. Therefore, an efficient provenance data management system is required to trace out the provenance information through provenance capturing and querying for social data generated from various social media platforms.…”

“…On the other hand, several illegitimate activities are engendered by misusing these social content through social engineering [18,19,56] to accomplish various objectives. One of the main causes behind the illegitimate activities on social media is the separation of digital content from its provenance [12]. In this paper, our second motivation is to explore the need of provenance information associated with the digital content published on social media and to design an efficient social data provenance framework for key-value pair (KVP) database.…”

Social data provenance framework based on zero-information loss graph database

“…In present digitized world, everyday a huge amount of digital content is generated by various social media platforms mainly through mobile devices and shared with other users (Kaplan and Haenlein 2010;Corsar et al 2016;Feng et al 2018). In this way, social media has been playing a major role in information sharing at a large scale due to its easy access, low cost, and fast dissemination of information.…”

“…Hence, to rebuild the trust, there is a need to restore the concept of data provenance (Buneman and Tan 2019;Cheney et al 2009;Glavic and Miller 2011;Bearman and Lytle 1985;Herschel et al 2017;Buneman et al 2000;Buneman and Davidson 2010;Simmhan et al 2005;Yuan et al 2018) in social media. Social data provenance is the only way through which social media can regain some semblance of trust from their users (Corsar et al 2016;Feng et al 2018;Markovic et al 2013;Riveni et al 2017). In this paper, our main motivation is to explore the need of provenance data associated with digital content published on social media, and to design an efficient social data provenance (SDP) framework based on zero-information loss graph database (ZILGDB).…”