Sentiment Analysis and Classifying Hashtags in Social Media Using Data Mining Techniques

Big data is one of the important topics which is still open for a wide range of applications for extracting useful information and knowledge for supporting organizations by planning and decision-making. Social media as a technology is an important resource of data, especially because it has been widely used in the last years. A Hashtag is recently one of the most popular features provided by Social media and is used by most social media users to express, share, and retrieve opinions and feelings regarding a specific theme. Hashtag features in social media are used more and more in recent years to discuss and debate important current events by public audience. This paper sheds light on how business can use such sources of information and how needed technical processes can be implemented accordingly. The paper demonstrates sentiment analysis as a scenario for such implementation. The main innovation in this paper is not limited to the technical method used, but rather to focus on the idea of using hashtags as information source in business, which is still rarely addressed in science. This paper will provide a novel model based on text mining techniques to provide a sentiment analysis for classifying business-related Hashtags posted on social media from the customers. The results will be presented and verified through samples of positive, and negative classified comments extracted from the Hashtags for supporting the organization by planning and decision making for generating completive advantages

Investigating the Success and the Advantages of Using ERP System in KSA Context

Enterprise resource planning (ERP) is an important innovation, affecting the business world by generating improvements both tangible and intangible in large companies and small and medium enterprises (SME). This study focuses on the determinants of success and the advantages of the adoption of this technology. To address these points, a comprehensive literature survey was carried out in order to formulate an original research model for ERP success evaluation and provide a prospect for IT infrastructure and integration. The model, thus suggested and taken within the Kingdom of Saudi Arabia (KSA) context, examines in a systematic approach the relation between the ERP acceptance determinants, the effects of the process of ERP systems diffusion, and the impacts expected on organizational performance. Obtained results underline two key determinants of ERP projects success: First, the preponderance of information control and the improvement in the use of competences. The second factor is the quality of team projects, the definition of team’s mission, training, business processes reengineering, user acceptance, top management support and the selection of the ERP solution

Development of a Luminescence Immunoassay for Follitropin Suitable for Clinical Routine

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