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.

Purpose: To analyze the reasons for which users select retrieved images from Google Search engine and investigate the relationship between users’ demographic variables and criteria for relevance judgment.Methodology: Thirty (30) graduate students in school of Engineering of Ferdowsi University of Mashhad were surveyed. Data gathered using a questionnaire asking about the reasons for selecting images and users’ relevance judgment. Objective criteria were obtained from related literature and validated by a number of experts.Results: There was no significant correlation between individual characteristics (experience and skill, educational level, age and gender) and users’ views toward the objective relevance criteria. The “user’s overall impression that an image may be useful” with 100% agreement was the main reason for image selection and the “uncertainty and going for the next image” with 33.33% was the main reason for rejecting an image.Conclusion: Users select images based on their overall impression, mental experience and their knowledge. The relevance judgment by users is not related to their familiarity with web elements.

Objective: With the development of the web, image Search is considered to be one of the most important approaches and one of the major challenges for users. On the other hand, relevance as a cognitive concept has always been of interest and dates back to the time when one tried to retrieve and make good use of information. The inadequacy of the algorithmic approach proved that it is only the user himself who can judge the relevance of the document to its need and use. As a result, mental attitude has replaced military relevance in relevance studies. The purpose of this study is to investigate the viewpoints of graduate students of Ferdowsi University of Mashhad on subjective and objective criteria of relevance judgment in image retrieval from Google Search engine in order to provide solutions to improve the retrieval approach in image retrieval systems. Methodology: This is an applied reSearch using survey method. The statistical population of this study is graduate students of Ferdowsi University. Thirty male and female of BA, MA and doctoral students from various faculties of Ferdowsi University of Mashhad formed the sample of this study. The reSearch data were collected through a questionnaire consisting of four sections. The first and the second part of the questionnaire before the beginning of the Search session and the third and fourth part of the questionnaire after the end of the Search session were given to the subjects. In this regard, subjective and objective criteria of judgment of the users in relation to the images were studied in order to determine with what criteria the users judge the relevance of the images and make their choice. Findings: The findings showed that, in both subjective and objective judgment stages, except for "subject" criteria, "updating", "image attraction", "accessibility" and "information quality" criteria were important. The most relevant criteria for judging students regarding the relevance of images retrieved in Google's Search engine were identified. In addition to the stated criteria, it was observed that the users focused on the "information effect" with emphasis on criteria such as "interesting" and "enjoyable" and the average score above these criteria indicates their importance. The findings also indicated that users place less importance on the creator(s) of the image as a specific criterion in the web environment, and these criteria are not among their top priorities in information selection. In general, it can be said that the judgment of the user on the basis of their needs, feelings and situation is very important. It is recommended that further reSearch be carried out in order to obtain new findings in order to assist in the design of more efficient and more appropriate image Search engines that are consistent with user behavior and characteristics. Conclusion: What distinguishes the present study from other studies is the image Search approach that has been studied with emphasis on Iranian users, Google Search engine, and in two stages of subjective judgment and objective judgment that differs from the other reSearches.

This comparative study addressed user satisfaction of Unassisted Keyword Search Paradigm with Assisted Keyword Search Paradigm in the Google Search engine. The methodology was one group pretest-posttest design. The instrument for data collection was 3 reSearcher-made questionnaires that one of them included closed questions about expertise in using computer and the Internet as well as demographic information.Other questionnaires were process-based forms which dealt with Search questions, Search procedures and evaluation forms for each state. The subjects under study were postgraduate students of Foreign Languages and Linguistic Department of Shiraz University, 30 students were selected by using the propotional random sampling technique and non- random technique was used for whom didn’t participate.Findings of the study revealed that about 70 percent of suggestions presented in Google Suggest Beta as an assisted keyword Search server had a middle-to-higher relevance. Although there was no significant difference between precision based user oriented relevance in both of paradigms, assisted keyword Search led to a significant increase in precision on based system oriented relevance. Generally, the second paradigm caused a significant increase in both the ease of use and the whole performance of the system in finding expected results .Although there was not seen any significant difference between time satisfaction and Search results' value, the total user satisfaction increased significantly in the second paradigm. Finally, some suggestions for futher studies were provided.

Information and resources available on the Web are growing increasingly and web users need to have a common understanding of them. The Semantic Web whose most important role is to help machine to understand and analyze the existing data on the Web, has not been used commonly, yet. The foundation of the Semantic Web are ontologies. Ontologies play the main role in the exchange of information and development of the Lexical Web to the Semantic Web. Manual construction of ontologies is time-consuming, expensive, and dependent on the knowledge of domain engineers. Also, Ontologies that have been extracted automatically from corpus on the Web might have incomplete information. The main objective of this study is describing a method to improve and expand the information of the ontologies. Therefore, this study first discusses the automatic construction of prototype ontology in animals’ domain from Wikipedia and then a method is presented to improve the built ontology. The proposed method of improving ontology expands ontology concepts through Bootstrapping methods using a set of concepts and relations in initial ontology and with the help of the Google Search engine. A confidence measure was considered to choose the best option from the returned results by Google. Finally, the experiments showed the information that was obtained using the proposed method is twice more accurate than the information that was obtained at the stage of automatic construction of ontology from Wikipedia.

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.

Purpose: The study purpose was to determine and compare the Recall and Precision of Bing and Google Image Search engines for content based image retrieval. Methodology: The reSearch used webometrics and comparative methods. Population includes images stored in the databases of Bing and Google Search engines, and reSearch sample includes 15 selective images Searched in any of Search engines. All the retrieved sources through the images by image content based image Search were gathered, results’ Recall and Precision measures were calculated by relevance formula and their average percentage were obtained. ReSearch hypotheses were tested by U Mann-Whitney test as well. Findings: Findings showed that the Google Search engine functionality was higher with recall measure of % 88. 73 than recall rate (%20. 86) for Bing. But Bing Search engine had higher precision (% 99. 86) than Google (%94. 80). Results: Hypotheses tests on recall and precision in two Search engines’ image retrieval showed a significant difference for recall in favor of Google, indicating its better functionality than Bing but there was no significant difference between them concerning precision since both showed fair precision however Bing was relatively useful.

Considering the growth of digital marketing, the present study was conducted by webometrics approach. In this study Iranian university library websites are analyzed from the standpoint of Google Search engine optimization (SEO). Moreover, identifying the effective factors of Google SEO is done. The number of 30 effective components on Google SEO was obtained by using the agreement between two intelligent online SEO analysis tools ‘SEOsitecheckup’ and ‘SEOPtimer’, with a reliability coefficient of 0. 77. The number of 17 components were identified with the help of texts and the library method (the numbers of 12 components were common in both methods). The reSearch community consisted of 42 library websites of Iranian universities affiliated with the Ministry of Science, ReSearch and Technology located in major cities of Iran. The data collection tools were the online analysis databases ‘SEOptimer’, ‘Ahrefs’, ‘Similarweb’, and ‘W3 Consortium’ (in addition to the checklist and identified components). The members of the community were analyzed from the standpoint of the 34 measurable components by SEO analysis tools (no need for the manager or administrator of the same website) on the cross-sectional study for six months at the beginning of the year 2020). ‘Excel’ and ‘LibreOffice Click’ software were used to analyze the data. None of the websites of Iran's university libraries got the final SEO score of 75 out of 100. Only thirty-three percent of Iranian university library websites had observed the ‘digital security certificate’ effective component on SEO. The websites of the central library of Sharif university of technology, and the digital library of Shahid Beheshti university were ranked respectively, from standpoint of the final Google SEO score. Connecting the website to various social networks such as LinkedIn, Facebook, and Instagram, is necessary to improve Google's SEO score, but it is not sufficient (only one effective component). The components affecting Google SEO can be divided into two groups. The first category can be adjusted by the administrators of the library website (including 29 components of the checklist offered in this present study and 1 component of the library website's compliance with the rules of the W3 consortium). The second category (including 4 components: ‘bounce rate’, ‘average visit duration’, ‘number of pages indexed in Google’, and ‘number of clicks or visits of uses) can be measured by the feedback of other websites or clicking of the users. Improving SEO-effective components along with having rich content will be valuable together with each other.