The purpose of this research is to investigate the status and the evolution of the scientific studies on the applications of social media in the business. The present research is an applied scientific method based on quantitative approach by using library method and scientometrics indicators. With the use of bibliometric library of R software, scientific products in the field of social media applications in business from 2005 to the end of January 2019, the study overviews trends and achievements of this field. The results show that from the beginning of 2005 through January 2019, 2682 articles have been indexed in Web of Science in the field of social media and business; however, since 2009, scientific productions in this topic have grown rapidly and in 2017, there was a substantial increase in the number of studies. The findings also show that the United States with 1269 published articles and the Business Horizons Magazine with the publication of 73 articles, pioneered in the publications of this topic. Analyzing the content of the works produced in the applications of the social media and businesses can help us better understand the growth trend in this area.

In this study, the efficiency of integration between Taguchi and TOPSIS in multi-response optimi-zation of powder mixed electrical discharge machining (PMEDM) process was evaluated. The in-put parameters, such as workpiece and tool electrode material, polarity, pulse on time (ton), pulse off time (toff), Current (I) and powder concentration have been selected to optimize two responses; namely surface roughness (Ra) and surface hardness (HV). The results show that titanium powder mixed dielectric fluid improves multi-response optimization efficiency in PMEDM. In addition, machining conditions, such as tool electrode material, powder concentration, pulse on time, polarity, current density, A×G and B×G interactions play a very important role on S/N ratio of C* whereby powder concentration has the strongest influence. TOPSIS -Taguchi is a potential method for multi-response optimization in PMEDM. However, the optimal results using ANOVA analysis show that there is a necessity to have more studies in TOPSIS-Taguchi to improve the in-tegration efficiency between two methods for optimizing multiple responses in PMEDM.