Review of social media analytics process and Big Data pipeline

Social media analytics is a research axis focused on extracting useful insights from social media data, with the aim of helping individuals and organizations take the most optimum decisions regarding several disciplines of life (business, marketing, politics, health, etc.). In this respect, social networks, microblogging, and media-sharing websites represent striking instances of online social media, as constructed under the Web 2.0 associated technologies, targeted to promote the interaction between users and these websites, while shifting the user’s position from that of a mere consumer to that of a social data producer. Hence, huge amounts of social data turn out to be issued, thus turning into critical sources of Big Data. Actually, the traditional media analytical techniques seem obsolete and inadequate to process this huge array of unstructured social media and capture the massive data range, mainly the shifting from the batch scale to the streaming one. Such a process has culminated in injecting Big Data technologies throughout the analysis process. So, the present survey is targeted to help the concerned researchers identify the challenges encountered during the analysis process along with Big Data solutions. Indeed, the aim lies in providing a clear analytical process applicable with Big Data technologies. A systematic literature review is conducted to address the challenges facing integration of Big Data technologies, while displaying some adequate solutions. Following extensive literature search, an overall global view concerning the superposition of the social media analytics and Big Data technologies has been drawn and discussed, along with a promising potential research trend.