پژوهشنامه پردازش و مدیریت اطلاعات
سال سی و هشتم شماره 4 (پیاپی 114، تابستان 1402)

Plagiarism as a clear example of academic corruption violates research ethics and slows down the production of science. Despite the criminalization of plagiarism in the Law on the Protection of the Rights of Authors, Writers and Artists, the quantitative nature of research in Iran has led to the growth of this behavior. Due to the importance of the discussion, this study aimed to investigate the relationship between the control source and research ethics in the prevention of plagiarism. The statistical population of the study is all members of the group and the Telegram channel of the School of Criminal Sciences as experts in Iranian criminal law, of which 212 people were selected as the final volume using the Cochran's formula. The data collection tool is the Ratter Control Source Questionnaire in which internal and external controls are checked. Also regarding research ethics and plagiarism, a researcher-made questionnaire design and their face and content validity using the opinions of three experts confirmed and their reliability for research ethics and plagiarism questionnaires with Cronbach's alpha coefficient of 0.82 and 0.87 was calculated .According to the findings, there is no relationship between internal and external control and prevention of plagiarism. Given that external control is used to justify unsuccessful behaviors and that not committing a crime is a successful behavior, the lack of a link between external control and plagiarism prevention is justified, but the lack of a link between internal control and plagiarism prevention suggests that self-control and morality have no role in preventing plagiarism. Thus, it can be said that the criminalization of plagiarism and the development of intelligent plagiarism detection software such as the software of Iranian Research Institute for Information Science and Technology by increasing the costs of crime has led to deterrence. The findings also show that the variables of research ethics, age, academic status and employment status have a significant positive relationship with the prevention of plagiarism. This means that crime prevention is better guaranteed by increasing the age, improve academic standing and promote research ethics. However, studies show that gender has a significant negative relationship with the prevention of plagiarism. This means that women are more talented and willing to commit crimes. Findings from stepwise regression analysis also proved that among the five main variables, three factors of research ethics, academic status and gender are able to estimate crime prevention

Common points of convergence of information and communication skills, information literacy, information behavior, individual-collective creativity, intelligence, and cognitive-perceptual issues, in the category of information intelligence. Measuring information intelligence is very important in information societies. Addressing the effective indicators in this issue is one of the determining issues in the use of information and data in information societies. The present study aimed to identify indicators and measures effective in measuring information intelligence. The research is applied and uses a qualitative method including library studies, content analysis, and analysis of expert opinions. Data collection tools included the study of scientific literature related to the subject, content-coding, and interviews with experts familiar with the subject of information intelligence (8 experts in knowledge and information science and 7 experts in psychology). The research population included related published literature related to scientific theories, information science experts, and psychology experts. In the subject of intelligence, Gardner's multiple intelligence theory has been used, and in the subject of information-seeking behavior, various scientific theories have been used. Based on the research findings, 14 indicators and 97 measures were identified as effective for measuring information intelligence in two dimensions management and information retrieval. Finally, a proposed framework is presented for measuring information intelligence. From the findings, it was concluded that in the information society, policymakers and managers of the organization or responsible organizations in relation to increasing the level of information intelligence of the society, should consider the specific strategies of the information intelligence of the society in formulating their general strategies. One of these strategic goals can be to increase the level of information intelligence of individuals, organizations, and society. To do this, effective indicators must be identified for measuring and strategies to increase the level of information intelligence of the target community. It is suggested that this matter is placed in the priorities of the information society and the native measurement tool of information intelligence can be prepared based on the findings of this research.

In this research, the activity of Twitter s users has been analyzed. The sample of the research was the users who posted on the topic of technology. The purpose of this research was to present the process of using the data of Twitter s users in the policy making process. This process has suggested how to use data analysis in each step of the policy making process. Algorithms presented in this process were tested with 6-month data of all Persian language Twitter s users who have published tweets on the topic of science and technology policy. The proposed classification model was able to distinguish and separate evidence tweets from non-evidence tweets with acceptable accuracy. Also, the text of the tweets of the most influential Twitter users who posted tweets and the number of connections their tweets created were extracted and analyzed. The selection criterion of these users was the number of connections they had made (more than 300 connections), which shows that these users have paid the most attention to information filtering, applications and social networks. The innovation of this research was the proposal to use the data of social network users in the policy making process.

Creating an information security culture helps to minimize threats, especially threats caused by humans, in order to protect information, and as a result, it leads to the reduction of data breaches or incidents in organizations. No study has been conducted to identify the components of information security culture in the country so far. Information security culture has been investigated and analyzed using different approaches and based on different theories. The purpose of this article is to review the existing researches in the field of information security culture in order to investigate the knowledge resulted and identify the dimensions and components of the information security culture and integrate the literature in this field.
In order to carry out this systematic review, all the studies conducted in the field of information security culture were extracted from reliable databases using relevant keywords. Finally, 310 related articles from 2000 to 2022 were reviewed. Based on the results of this study and according to the purpose of the research, the components and dimensions of information security culture with different approaches and perspectives were identified and compiled.
The research findings indicate that there is no widely accepted set of dimensions and components. Different researchers have considered different dimensions and components for the information security culture. They have used 3 theories and concepts in their studies. The frequency of theories used in different researches was determined and the most commonly used one is Schein’s organizational culture model. Also the mentioned researches have been carried out in various organizations and industries. There is no industry-specific model or framework provided. Also, most of the proposed models or frameworks are descriptive and have not been evaluated, and in terms of geographical division, the researches were also examined and it was found that most of the researches belong to developing countries

In the world of continuous changes, digital transformation has emerged as an inevitable factor for survival of organizations. Not only it is a technology change, but also is a radical change in all aspects and in other words is a business transformation. Banks like other organizations in digital era are facing new features namely the emergence of disruptive technologies and new business models, presence in ecosystems and importance of customer experience. In order for revising an enterprise architecture with digital transformation approach, it is required to determine the distinguishing characteristics of digital banks and traditional banks. The reason is that such characters affect the enterprise architecture framework approach and also the school of thought of enterprise architecture.  Design/methodology/approach: In the current research, we applied the mixture of quantitative and qualitative research method. firstly, using a systematic literature review, 284 papers with related keywords with digital bank were reviewed in order to extract the distinguishing features of this bank with traditional banks. In order for determining the indicators and their categories using the SLR, alongside a researcher (coder 1) is done by another expert of SLR (coder 2). Considering the KAPA coefficient 804%, six major features of digital banks are as follows: customer-centric experience, service oriented, based on ecosystem, alignment with digital technologies, digital transformation strategy, and platform oriented codded as 18 micro features. For finding the enterprise architecture school of thought and enterprise architecture framework aligned with digital banks, a questionnaire was designed by a group of 27 experts of enterprise architecture and digital transformation.  The results of findings were analyzed using SWARA-WASPAS method. The results show by considering the macro and micro characteristics of digital banks, in order for implementing a digital bank architecture, considering the distinguishing characters of the bank, it is essential to select ecological school of thought and service-oriented framework.

The purpose of this research is to investigate the interaction of Users (graduate students of Kharazmi University) with Ganj database in order to evaluate the performance of this database according to the honeycomb user experience Model. It is expected that the results of this study can help to solve the existing interactive difficulties while identifying the status of effective elements in the user experience in interacting with this database. This research is practical and was done by survey method. The research tool was a questionnaire that was designed using 7 components of the honeycomb: the usefulness, accessibility, usability, searchability, validity, desirability and value of the Iranian scientific database (Ganj). Analysis of research data were performed using descriptive and inferential statistics and SPSS software. Also we used Amos software to confirm the research model using path analysis method.  Findings showed that there was a great positive effect between accessibility and usability, usefulness and availability, desirability and credibility of the Ganj database; That is, with increasing the amount of accessibility variable, the amount of usability variable and with increasing the amount of utility variable, the amount of accessibility variable and vice versa increases. As a result, if the Ganj database is not accessible, the usability and usefulness of this database, which aims to publish information for researchers, as well as the usefulness of the services provided to researchers by this database will be reduced. As the desirability variable increases, the validity variable increases and vice versa. As a result, if students are dissatisfied with the features of desirability (appearance design, design capabilities of search components ...), their trust in the database will be lost and the credibility of the Ganj database in providing better services will be reduced. From the findings of this study, it can be concluded that the variable "value" as a strong and powerful variable has a direct and indirect positive effect on other research variables. This finding shows that if a database like Ganj does not create value for users, other components related to the user experience will not be in a good condition, and vice versa. Among these, the accessibility variable is also of special importance, which affects other variables in the Ganj database. As a result of not having access to the Ganj database, the usability of this database is reduced. If the capabilities of using the Ganj database are compromised, the credibility and usefulness of the Ganj will be reduced, and therefore users will lose their trust in this database, and the work with Ganj will not be satisfactory and useful for its users.

This article presents a method to find the number of topics in Persian research articles, which is actually one of the main challenges in topic modeling. It is the process of automatically recognizing topics in a text with the aim of discovering hidden patterns
This study has estimated the number of topics for Persian research articles using two approaches. The first is based on the greedy search and later uses Renormalization theory, which is a mathematical formalism to construct a procedure for changing the scale of the system so that the behavior of the system preserves. Also, the execution time of both algorithms on Persian academic articles has been compared with each other.
The findings indicate that the renormalization approach predicts the number of topics in Persian research articles with the lower time complexity in comparison to the greedy based approach.
The approach based on Renormalization has high efficiency for estimating the number of topics in Persian academic articles.

Keyword extraction is one of the most important issues in text processing and analysis and provides a high-level and accurate summary of the text. Therefore, choosing the right method to extract keywords from the text is important. The aim of the present study was to compare the performance of three approaches in discovering and extracting the subject keywords of e-books using text mining and machine learning techniques. In this regard, three experimental approaches have been introduced and compared; including the successive implementation of the clustering process, improving the quality of clusters in terms of semantics and enriching the stop words of a specific field; Use of specialized keyword template; Finally, the use of important parts of the text in discovering and extracting key words and important topics of the text. The statistical population includes 1000 e-book titles from the subject fields of library and information science based on the congress classification system. bibliographic information of EBooks was obtained from the congress library database, then the original text was prepared. The extraction of topic keywords and clustering of training data was performed using the non-negative matrix factorization algorithm with three experimental approaches. The quality and performance of the subject clusters resulting from the implementation of three approaches in the automatic classification of experimental data were compared using a support vector machine. The findings showed that the Hamming loss (0.020) and in other words the error rate in the correct classification of experimental texts in the third approach is far less than the other two approaches. Also, the F1 score (0.82), which is the average of the two criteria of Precision (0.87) and recall (0.78) and is a reflection of the correct performance of the classification process in topic labeling of texts, is better in the third approach than the other two approaches. The results showed that the quality and semantic coherence of the subject clusters obtained from the third approach, ie the use of important parts of the text in discovering and extracting the subject, was better compared to the other two approaches. In this approach, by focusing on the main parts of the data, which represent the main content and theme of the text, more meaningful topic clusters were obtained. In addition, the keywords obtained from the topic cluster of the third approach can be used in unspecified and unknown collections in order to extract the unknown thematic content of the whole collection. The results of third approach also was better in terms of accuracy and readability (0.79) and the rate of classification error (0.020) of texts, in comparison of other two approaches.

The research aim is identifying criteria for determining and evaluating scientific articles subject terms from pragmatic perspective. From pragmatic perspective, it seems the correctness of scientific articles subject terms depends on having functions including representationality and  usefulness, simultaneously. One of the criteria for evaluating the functions of articles subject terms is users’ language. To evaluate the functions of scientific articles subject terms by users’ language we need to identify common points among users’ language and relevant articles to their information needs. This research has done by decompositional analysis. These common points were identified according to user’s roles in information searching and using (user as searcher; user as citer; user as tagger). These common points are: a) All search terms that a certain article could response to them; b) Common terms between cited and citing articles that are available in the semantic sources of citing articles; c) Terms that are available in the semantic sources of article and used by citer in citation context; d) Tags dedicated to scientific articles by users through social tagging websites. This research concludes although each of user’s linguistic traces (user as searcher; user as citer; user as tagger) in the route of attaining articles relevant to her/his information need having possibility to be considered as a subject access points for those articles, but from the perspective of information use as information production faces challenges.

Currently, in the researches of library and information sciences, the relationship between the process of searching and learning is discussed a lot. It seems that the search to learning has led to exploratory search and exploratory search has helped users discover concepts in order to overcome their uncertainty and finally, achieve learning. What has been neglected is the extent to which searching process affects learning and the degree of knowledge change until one reaches the level of expertise. Hence, the present study was compiled on research findings with the aim of determining the impact of the information search process based on work tasks on learning. For this purpose, a semi-experimental one-group design with pre-test and post-test was used in 2021. The statistical population was the nursing students of the Bushehr University of Medical Sciences in their sixth semester, and 38 of these students randomly participated in this study. First of all, an educational workshop with the aim of getting familiar with drawing conceptual map and a search training workshop were held. Afterwards, the students were assigned two tasks and they were asked to draw their conceptual maps before and after searching. In order to describe and analyze the information in this research, conceptual map scoring (a type of quantitative content analysis) was used to determine the degree of learning, the Euclidean algorithm was used to assess the degree of knowledge change until reaching the level of expertise, and the pairwise comparison method was used to evaluate the difference in the degree of learning before and after the search. The outcomes indicated that the mean difference before and after the search was significant in both scenarios (P<0.001). Also, there was a significant difference between the mean scores before and after the search and the score of the conceptual map, with high confidence. However, it was low, compared to the rate of learning growth according to the expert score. Besides, the difference between the mean of the conceptual map in the complex and simple scenarios was not significant. The results demonstrated the effectiveness of search as a learning method, so it is suggested that librarians and information professors introduce searching as a learning method along with other methods to increase awareness and develop creative thinking skills in the academic community.

The Internet of Things is becoming a key element of the future Internet and a vital national and international infrastructure, and it seems that the introduction of the Internet of Things in libraries is imminent and inevitable; Therefore, the identification of the architecture of using the Internet of Things in Iranian academic libraries is the most important concern and the main problem of the present research, which according to the searches carried out so far, the comprehensive architecture based on the systematic review of studies, architectures, previous models and the combination of findings They have been designed, it has not been presented for university libraries in Iran, so this research can be the beginning of exploiting this emerging technology. Based on the purpose, the type of research is developmental-applied, and in terms of the execution path, meta-composite, survey-analytical methods and the approval of subject experts have been used. The databases of Elsevier, Scopus, Emerald, LISTA, IEEE Xplore, Migran, Noor Specialized Journals Database, Civilica, University Jihad Scientific Information Center Database, and Google Scholar Search Engine were reviewed. In the first stage, after reviewing the mentioned databases, the researchers extracted the components and indicators of IoT application, which have 9 components (building, management, users, librarians, lending, reading room, reference, cataloging, information literacy) and 31 Indicators for architectural design and operational pattern were identified. In order to confirm these components and indicators from the point of view of the target community (administrators of university libraries in Iran), a researcher's checklist was sent to them. The meaning of these libraries is the central libraries of comprehensive universities, which were studied in the census method and after examining the results of the one-sample t-test, it was determined that all the components and indicators for use in university libraries in Iran are approved by the society. The target is located. Then, with a comprehensive review of these previous researches, a proposed architecture that is comprehensive and clear was designed and approved by experts in the field of Internet of Things. The proposed architecture consists of five layers: device, network, middleware, services, security and privacy, and the working method of each layer is described. If the managers of these libraries have a desire to use the Internet of Things, they can use this proposed architecture for the basic principles of their work.

Countries are adjacent or opposite in physical, political, economic, social, cultural, and scientific dimensions. Proximity or distance among countries in terms of the above dimensions can cause or prevent strong inter-country scientific collaboration. The objectives of this research are primarily to identify the dimensions that better explain the intensity of international scientific collaboration, and secondly, to investigate the fluctuations in the intensity of the influence of each dimension over time. To achieve the above-mentioned aims, and based on the integration of proximity literature with the CAGE distance framework, the determining factors of international scientific collaboration were extracted. The population of the research consisted of 167 independent countries in the period of 2002-2017. In this research, the network of co-author relations between countries is considered as an indicator of international scientific collaboration, whose data was collected from the Web of Science database. Also, data on proximity dimensions were collected from various databases (United Nations, International Trade Center, etc.). This research has an explanatory nature and is based on the analysis of secondary data with a quantitative approach (a gravity model). Model effects were estimated using R package fixest. The application of this model showed that the intensity of international scientific collaboration has a positive relationship with proximity and a negative relationship with the distance between countries in different dimensions. The findings obtained from the comparison of the explanatory power of the proximity dimensions indicated the high explanatory power of social proximity. Nevertheless, the findings of the model improvement showed that the simultaneous presence of the political, economic, and social dimensions also have an explanatory power close to that of the social proximity. Examining the fluctuations in the influence of proximity dimensions over time showed a significant increase in the influence of proximity in economic, social, and scientific dimensions, a common language in the cultural dimension, intra-regional collaboration, and collaboration between neighboring countries in the physical dimension. Meanwhile, the influence of geographical distance in the physical dimension, colonial relations in the political dimension, and religious and ethnic commonalities in the cultural dimension have decreased significantly. It is only in the political dimension that the effect of most factors is partial (such as the difference in terms of the degree of realization of the liberal democratic government or the efficiency of the government, and the imposition of sanctions against the other party) and sometimes is fixed (such as common membership in international agreements).

All organizations use data to execute their processes. Organizational data is either generated by the organization itself or created and provided by other organizations. Data and information play an essential role in the decisions and functions of organizational processes. For this reason, data is part of the organization's resources and perhaps the most important source of organizations. The purpose of this study was to provide a data quality model for data governance. The research method was used in a meta-combination. Therefore, out of 268 sources found, during the meta-combination process, 62 articles were used using keywords such as; Data, data management, data governance and data quality management were selected in Irandak, Science Direct, Google Scholar, Springer, IEEE and ACM databases between 1995-2022. In this study, first a code was considered for all factors extracted from previous studies and then, considering the concept of each code, they were classified in a similar concept. In this way, the concepts of research were identified. Two coders were used to control the extracted codes and categories, and the desired index in this field is the kappa index. Based on the analysis performed using the content analysis method, a total of 12 main categories ("data attribute, data, data fable, data value, initial data value, data pattern, data set, data access, data composition, data formatting, Metadata and data objectivity ”) and 47 sub-categories for data quality management for data governance were identified and identified.