The purpose of this research is to study the role of the social media for knowledge sharing. The study presents a comprehensive review of the researches associated with the effect of knowledge management in social media. The study uses Scopus database as a primary search engine and covers 1858 of highly cited articles over the period 1994-2019. The records are statistically analyzed and categorized in terms of various criteria using an open source software package named R. The findings show that researches have grown exponentially during the recent years and the trend has continued at relatively stable rates. Based on the survey, knowledge management is the keyword which has carried the highest citations followed by social media and social networking. Among the most cited articles, papers published by researchers in United States have received the highest citations, followed by United Kingdom and China.

The purpose of this research is to investigate the status and the evolution of the scientific studies for the effect of social networks on big data and usage of big data for modeling the social net-works users’ behavior. This paper presents a comprehensive review of the studies associated with big data in social media. The study uses Scopus database as a primary search engine and covers 2000 of highly cited articles over the period 2012-2019. The records are statistically analyzed and categorized in terms of different criteria. The findings show that researches have grown exponentially since 2014 and the trend has continued at relatively stable rates. Based on the survey, decision support systems is the keyword which has carried the highest densities followed by heuristics methods. Among the most cited articles, papers published by researchers in United States have received the highest citations (7548), followed by United Kingdom (588) and China with 543 citations. Thematic analysis shows that the subject nearly maintained an important and well-developed research field and for better results we can merge our research with “big data analytics” and “twitter” that are important topics in this field but not developed well.

Social media has grown very quickly and has affected all dimensions of the world’s community. The purpose of this article is to review valid articles on the relationship between social media and promotion using manual and bibliometrics analysis methods and identify top themes in these articles. We review the papers published between 2007 and the first month of 2019 in Scopus. 1,840 articles were published in the mentioned period. In this article, we review various charts including word dynamics, the contributions of different countries, country scientific production, corresponding author's country, the frequency distribution of sources, collaboration network and country collaboration map. The study indicates that Canada, Australia and France were the most productive countries in this area.

This paper presents a comprehensive scientometric study for the impact of social networks on advertisement. The study uses the Scopus database as a search engine to accomplish the survey. To better understand the evolution and identity of this category, the study covers 1216 most cited data over the period 1983-2019. Qualitative and quantitative data analysis techniques are applied to determine author distribution, country, individual and institutional-level productivity rankings. In terms of keywords, the study indicates that social media was jointly studied with gender and be-havior and researchers from the United States maintained the highest rate of contribution. The survey also indicates that there were strong collaboration between the researchers from China and United States. Moreover, there were also remarkable collaborations between the researchers in United States from one side and other countries.

Social media has grown steadily during the last decade and it is now considered as a new opportunity to use for different purposes such as decision making. The primary objective of this paper is to review articles related to social media and decision making using manual and bibliometrics anal-ysis methods, and to identify top themes in these articles. We have reviewed the papers published between 2008 and the first month of 2019 in Scopus where 1,159 articles were published in this period. These articles come from 733 sources and 3,459 authors. According to our survey, United States is the most productive country. Moreover, most collaborations occurred between two coun-tries of United States and United Kingdom as well as between United States and China. The bibliometrics analysis examines global research in this field from the different point of views.

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.

The purpose of this research is to provide a conceptual overview on published studies and articles related to social media and information systems as two independent, continuous and interdepend-ent concepts. The research data is from the survey for two social media keywords and information systems from the Scopus site, which is one of the main scientific search engines. Due to a large number of findings, the study area was limited to 6 major areas of social sciences, business management, economics, arts and humanities, psychology and decision-making sciences, and 5185 articles were found. To investigate and analyze the findings, the Romethometrics and bibliometrics library of R Studio software were used. Biblimetrix was a method for studying and evaluating quantitative scientific texts using mathematical and statistical methods. The data obtained from this research is useful for scholars, researchers, decision-makers and those interested in social media and information networks in the political, economic, social and cultural spheres.

The purpose of this research is to investigate the status and the evolution of the scientific studies on the effect of social networks on e-commerce. The study seeks to address the status of a set of scientific productions of researchers in the world indexed in Scopus based on scientometrics indicators. In total, 1926 articles were found and the collected data were analyzed using quantitative and qualitative indicators of scientometrics with bibliometrix R software package. The findings show that researches have grown exponentially since 2009 and the trend has continued at relatively stable rates. Thematic analysis shows that the subject had a significant but not well-developed research field. There is a high rate of cooperation with a rich research network among institutions in United States, European and Asian countries. Studies also show that research interest in this area is prevalent in developed countries. In addition, the lack of funds and complex analytical tools may be due to lack of studies in developing countries, especially in Africa. The study of the global trend of research through scientometrics helps managers and researchers in identifying countries and institutions with the greatest potential for scientific production, which allows them to develop their professions.

Ti-6Al-4V Extra Low Interstitial (ELI) exhibits superior properties because of controlled interstitial element of iron and oxygen. The effects of four cutting parameters namely cutting speed, feed, depth of cut and tool nose radius on responses like cutting force, average cutting temperature and surface roughness have been investigated for turning of Ti-6Al-4V (ELI). Total 81 experiments have been performed in dry environment. Grey Relational Analysis has been used for multi-objective optimization. Analysis of Variance test has been carried out to investigate contribution of input parameters. The model was found fit with R-Square value of 88.74%. Regression and ANN models are developed for prediction and compared. From the Grey relational analysis, it is clear that optimum parameters to minimize cutting force, cutting temperature and surface roughness while turning Ti-6Al-4V (ELI), are cutting speed as 140 rpm, Nose radius 1.2mm, Feed 0.051mm/rev and depth of cut is 0.5mm. In comparison of regression model, the ANN model is found to be more accurate with average error of 3.57%.

Due to the increasing technological advances in all fields, a considerable amount of data has been collected to be processed for different purposes. Data mining is the process of determining and an-alyzing hidden information from different perspectives to obtain useful knowledge. Data mining can have many various applications, one of them is in medical diagnosis. Today, many diseases are regarded as dangerous and deadly. Heart disease, breast cancer, and diabetes are among the most dangerous ones. This paper investigates 168 articles associated with the implementation of data mining for diagnosing such diseases. The study concentrates on 85 selected papers which have received more attention between 1997 and 2018. All algorithms, data mining models, and evaluation methods are thoroughly reviewed with special consideration. The study attempts to determine the most efficient data mining methods used for medical diagnosing purposes. Also, one of the other significant results of this study is the detection of research gaps in the application of data mining in health care.