جستجوی مقالات مرتبط با کلیدواژه « vocabulary co-occurrence » در نشریات گروه « علوم انسانی »

The purpose of this research is to analyze and illustrate financial literacy articles, which have been investigated and identified semantic relationships between keywords in the field of financial literacy in the period 1964-2022 (unlimited) in the Web oScience database using vocabulary co-occurrence analysis and co-authorship. . Finally, 566 articles were extracted from the researched database and analyzed using Visweaver version 1.6.19 software. The results showed that the field of financial literacy is related to words such as education, knowledge, attitude, credit, performance, financial knowledge and self-efficacy, and the word "financial literacy" is the most frequent word in terms of frequency and has the highest co-occurrence with 186 occurrences. Based on the co-authored results of the countries, it was also determined that America, China and England are among the active countries in the world. Finally, the results of the co-authored map of the authors also showed that Losardi and Annamaria had the most cooperation. This study not only helps to expand the knowledge base about the research topic, but also helps to understand the evolution of financial literacy and related areas.

Studying the precise meanings and grasping the vocabulary of a text is an essential aspect of research in specialized fields like Semantics. Semantics, traditionally, examines how meanings have evolved, perceiving human language as a dynamic and continuous entity. This study delves into the semantics of the term "al-Amr" in the Quran through a historical-descriptive method, exploring the interconnected meanings and contexts of the term using the axes of substitution and co-occurrence. The findings suggest that the primary significance of "al-Amr" primarily revolves around work and command, with other meanings like subject, consultation, and advice identified as secondary meanings during the Jahiliyyah era. This term, along with its variations, is found 249 times in the Quran, with 78 occurrences in singular form, primarily appearing nominally and frequently co-occurring with the words "Allah and al-Rabb." In the Quran, "al-Amr" is a word with multiple meanings, encompassing 19 semantic facets, with twelve of these aspects achieving consensus. Some of its interpretations include "command, victory, punishment, sin, killing, conquest of Mecca, resurrection, revelation, denial, promise, Jesus son of Mary, decree, circumstance, drowning, abundance, death, consultation, caution, and fertility." The term "al-Amr" in the Quran can be categorized into three groups: matters concerning God, humans, or Satan, with the majority of occurrences of the word "al-Amr" being linked to God. Issues related to "those in authority and enjoining good" pertain to humans, while matters associated with Satan are connected to indecency and denial. When a matter is attributed to God, it signifies the negation of material objects, whereas when attributed to a creation, it denotes gradual existence within temporal and spatial constraints. When paired with the verbs "Qudia, Ata, and Jaa," it indicates punishment and retribution, and when paired with "Wabal" and the verb "Dhaq," it signifies sin and disbelief. Linking a command with providence conveys the concept of divine will and decree, and its correlation with the act of sending down implies revelation. Synonyms for al-Amr in the Quran include "Ahida and Wasiya," where, due to the necessity of implementation, these matters are used interchangeably with commands.

Hakim Jamal ad-Dīn Abū Muḥammad Ilyās ibn-Yūsuf ibn-Zakk ibn Muayyad Nizami Ganjavi is one of the great Persian poets whose valuable works, especially Khamse have influenced the poets who came after him. Due to his importance, Nizami has attracted the attention of writers and critics, and many books and articles have been devoted to him. In order to identify areas for further research relevant to Nizami Ganjavi’s works, it is necessary to obtain knowledge on the existing body of the research carried out on his works. Nowadays, one type of interdisciplinary research is the use of information science methods such as Co-citation, Co-word and Co-author Analyses in drawing the scientific map of a given field. The differences and similarities in each of these bibliometric research methods can lead to new and different information about the discipline under study. The present study intends to analyze all articles published on the subject Nezami using social media analysis techniques. This research is of descriptive-analytical type and has deployed Co-Word Analysis Approach. The corpus of the study is Persian articles on Nezami Ganjavi, indexed on authentic databases in the period between the years 1378 to 1399. To draw and analyze the co-occurrence network of words, "Ravar Matrix", "SPSS" and UCINET and Net Draw softwares are used, and the subjects are classified using the thematic clustering method. The results show that Khosrow and Shirin, Leily and Majnoon, Hafte Peykar, Makhzan al-Asrar, Iskandarnameh and Khamseh are the main subjects used in the keywords search, and Khosrow and Shirin is the most widely used keyword in papers.

The current research is practical in terms of its purpose, in which the method of content analysis and the use of co-word analysis, social network analysis, hierarchical clustering and strategic diagram were used.The community of this research consists of 2010 studies related to "Blockchain in the sharing of knowledge assets" in the period of 2002-2022 in the Web of Science database. Data analysis with hist-site, bib-excel, gefi and excel software; and the maps were drawn with VOS Viewer and SPSS software. The findings of the present study show the upward trend of productions and citations of this topic, so that 2021with 553 studies and 2020 with 5792citations respectively had the most productions and citations among the years under review. Also, through synonym analysis, 9 topic clusters were formed. The keywords "Blockchain, Internet of Things and Smart Contract" had the most frequency and the keywords "Blockchain, Internet and Security" had the most connections. On the other hand, the keywords "credit management, distributed databases and licensed blockchain" had the most citations. The term blockchain also had the highest co-occurrence in connection with terms such as smart contract, Internet of Things and security. Also, three clusters were formed in hierarchical clustering. These clusters were placed in the second and third regions of the strategic diagram. This research provides a framework of the main concepts and topics discussed in the research field of blockchain and knowledge sharing, which while creating a comprehensive perspective for researchers in this field, helps them in their research path.