A Critique Report on the Paper...

A Critique Report on the Paper: "A Unified Multidimensional Data Model from Social Networks for Unstructured Data Analysis" Authors: Hichem Dabb`echi, Nahla Haddar and Mounira Ben Abdallah (In Proc. of the IEEE/ACS 14th International Conference on
Computer Systems and Applications, Hammamet, Tunisia, 30 Oct.-3 Nov. 2017)

1. Introduction
   Now a day’s people use social medias to share their opinion using different social medals like Facebook, YouTube, Tweeters, Snapshot, and others. Millions of people across the world tweet every day, millions of people post multimedia data every day and millions of people read the post every day. Those multimedia data posted twitted and shared every day creates huge amount of unstructured social media data. Collecting those data and performing analytics on social media data stream is one of the main challenges of big data because very interesting business goal could be archived such as: addressing marketing strategies, profiling people tastes, targeting advertisements, and so forth [1].
   Collecting and managing data from various sources of social to provide meaningful business insight, Data ware house were developed for this unstructured multimedia data to analyses for decision makers. Researchers were proposed data model for this before this paper at different time, but none of the proposed model was unified, they all were specific to one media type. In this article the authors raised important topics of current issue and propose a unified social media multidimensional data model to analyze social media data. Their model was generic and dynamic that was not limited to specific social media.
   1.1 Problem identification
   The authors start by identifying the previous studies of unstructured data model for those huge data generated from social media. One of these studies was by L. Hannachi et al. [2], which proposed the online data analysis OLAP (Online Analytic Processing) tools which were used for numerous large data wares house, Nicolas et al. [3], also proposed Data ware house model to analyses large volume of tweet by processing measures in the context of knowledge discovery and Nafees et al. [4], Extend OLAP technology to allow multidimensional analysis of social media data by integrating text and opinion mining method.
   The above previous studies were basically focus to only one type social media that was twitter and were not inclusive of other social media. Online Analytic Processing tools were specific to one type social media and has a limitation of data size, post content analysis and post comments analysis. From this limitation the authors proposed unified model for all social media type and argued that standard Analytic Processing tools cannot handle this kind of huge complex multi-dimensional data arising in different types of social media. In this article the authors were proposed unified social media multidimensional data model to analyze social media like Twitters, Facebook, YouTube and others to fill the limitation gap.

2. Proposed solution
The main objectives of the authors were to design generic, dynamic and data model that were not limited to only specific type’s social media data. They try to include most popular and huge social media including Facebook, YouTube, Twitter and