The purpose of this study was situation analysis of books in the theoretical field of sporting event management in both Persian and English.The research method was applied in terms of purpose and descriptive in terms of strategy and quantitative content analysis in terms of implementation path. The statistical population of the study included all sports event management books in both Persian and English, which were indexed in March 2016 on the "Khane Ketab" and "Google Scholar" sites. Therefore, 70 Persian books and 50 English books were recognized and reviewed in total. The unit of analysis in this study included the title of books, cover of titles, editing, year of publication, number of authors, position of authors and publishers. The data collection tool was a coding sheet and coding instructions. The face and content validity of this instrument was confirmed by Cochran's test of 0.92 with the help of the agreement coefficient of 10 experts. Also, its reliability or objectivity with the help of Scott's pi test and determining the agreement coefficient of 2 coders at the rate of 0.83. Confirmed. The results showed that in terms of title, subject matter, edition and number of authors, there is no difference between Persian and English books, but in terms of dimensions, number of titles, year of publication, scientific position of authors and status of publishers, there is a significant difference between Persian and English books.

One of the most challenging and difficult aspects of translation is related to the translation of idioms by both machine systems and human translators. The problem arises from the recognition of the idioms on the one hand and translating them on the other hand. idiom recognition is not easy since an idiom may change its form based on the context in which it is used. Using systematic idiom collections and special rules to recognize idioms, the problem can be solved to a great extent. Moreover, the inclusion of a morphological as well as syntactic parser can greatly enhance the idiom recognition and translation process. The aim of this paper is twofold. First, we want to test Google Translate to see how well it is capable of translating idioms and next to provide means to improve the quality of translation of idioms by Google Translate.

The memetic mapping is a method to identify memes and categorize them in the form of a multilevel model. Meme is a reproducible cultural element and has been adapted from the concept of gene in the evolutionary biology. The purpose of this study was to describe the current culture of Google using memetic mapping. To this end, the printed and online texts published about Google were coded for memes. This way, 134 memes were extracted and reduced to 40 Memecules (a higher unit comprised of several related memes). Memecules were placed into 6 levels of organizational culture, namely fundamental assumptions, values, norms, artifacts, work procedures, and human resources procedures. Then, in order to understand the formation of Google’ s culture in the course of history, cultural genealogy method was applied. In this approach, the father of each meme (the culture from which the meme is adopted) is identified, and then the children are connected to their parents with an arrow. The outcome is a cultural genealogy model in shape of a family tree graph. In this study, 85 Greek and Indian cultures with impacts on the emergence of Google’ s culture were recognized and analyzed. This study successfully operationalized the meme concept and employed it in an empirical research. Memetic mapping is a powerful tool available for managers, consultants, and organizational researchers to explore the cultural phenomenon and to change it. Memetic engineering is capable of diagnosing and correcting a defective meme in a human community.

The main objective of this study was to investigate whether searching firm's ticker symbol and name in Google can predict its future stock market activities. In so doing, the data related to firms' ticker symbol and firms' name were collected using Google Trend and stock market activity was measured using four proxies, namely abnormal return, return volatility, stock trading volume and stock trading count. In order to meet the main objective of the study, multiple regression and panel regression were used over13082 firmmonth observation during the years between 2005 and 2018. The results showed that the future market activity, including return volatility, stock trading volume and stock trading count, increased with searching the firms' ticker and name in Google. However, there was no significant relationship between the future abnormal return and Google searches. Findings also showed that future market activity can be predicted using Google searches. In addition, there was a more significant relationship between the searched firms' ticker symbol than the searched firms' name and future market activity.

Google Translator Toolkit is one of the recent online translation tools made available to professional and non- professional users. This toolkit is an editing tool which enables users to edit the translations provided. by Google Translate. Google Translator Toolkit has several features which can make it interesting and at the same time useful for translators. First of all, it is rather easy to work. Second, its user- friendly interface allows users to easily edit the translations done by Google Translate, while at the same time provides access to existing translations done by other users. Last but not least, multiple users can work on a document and collaboratively translate it at the same time. The present paper elaborates on an observational study into the use of Google Translator Toolkit by a class of senior student translators at Allameh Tabataba'i University, Tehran, Iran in the context of translation of political texts from English into Persian. The results are drawn from the teacher's observation and the students' class discussions along with their answers to a questionnaire on the use of Google Translator Toolkit.

The aim off this research was to investigate user's query expansion in Google search Engine based on the "Cognitive Load Theory" and the extent and types of cognitive loads resulted from suggested keywords/queries presented in Google search engine. In this article, data were collected from 60 postgraduate students in Humanities/Social Sciences and Basic and Applied Sciences - at Ferdowsi University of Mashhad, Iran. Non- probability sampling - especially purposive sampling- was used as the sampling method. Also, individual sessions were administered with each of the students. Findings show that suggested keywords/queries and the retrieved pages do not make any significant problem (or negative cognitive load) for users. Also, there is no significant difference between students of the two fields of study regarding cognitive load in the query expansion process in Google. Approximately most of the suggested keywords/queries and the retrieved pages matched with users' needs and had direct relationship with their initial keywords. On the whole, the suggested keywords and queries have taken an appropriate approach regading more relevant results in this search engine.