Dr Saeedeh Ebrahimy, Dr Ghasem Salimi, Mrs Sahar Anbaraki, Mrs Hanieh Zare,
Volume 7, Issue 1 (6-2020)
Abstract
Aim: Scientific social networks were shaped as part of a set of social software and a platform for international interactions sharing the tangible and intangible knowledge of researchers. The purpose is to investigate the patterns and behaviors of knowledge sharing of researchers in Research Gate. Based on this, the question and answer system of this scientific social network was analyzed and reviewed.
Methodology: Method is applied descriptive survey with web content analysis approach. The community studied was the questions and answers provided in the Q & A system of Research Gate. Two subject areas were selected, 127 questions and 408 responses related to these two domains were analyzed and reviewed.
Findings: Findings showed that the questions raised in two domains examined in the question and answer system of the scientific network were conceptual questions and replies in both domains were often intangible, and the type of presentation are scientific vision and mental pattern. Most of the inquirers were researchers from Asian countries with less than 5 RG rank. While researchers from European countries - with an RG rank of over 10, have been posting answers and sharing their expertise.
Conclusion: Q & A systems are diverse, efficient technologies for sharing knowledge and enhancing international interactions among researchers beyond the geographical and political boundaries, which has created a place for the reproduction of scientific disciplines in the world. The results according to Castells, speak of latent power of social networks and question and answer systems in knowledge sharing and widespread knowledge boundaries that facilitate transfer of experiences, thought and knowledge of researchers and provide fertile ground for science.
Shabnam Refoua, Zahra Salimi,
Volume 8, Issue 2 (9-2021)
Abstract
Background and Aim: Scientific article recommender system assists and advance information retrieval process by proposing and offering articles tailored to the researchers needs. The main purpose of this study is to evaluate the performance of the recommender System in three scientific databases.
Method: This applied study is directed by the valuation method. Sample consisted of three scientific databases: Elsevier, Taylor & Francis, and Google Scholar, which share recommendation tools. "Information storage and retrieval" was selected as the search subject. Ten specialized keywords related to the topic of information storage and retrieval were selected. After searching each key words, the first retrieved article was reviewed. Then, for each first article, the first 5 recommended articles were mined in each of the three mentioned databases. Data was collected through direct observation using a researcher-made checklist. To evaluate subject relevance, bibliographic information of the first article retrieved in each subject and database along with the bibliographic information of 5 recommended articles was provided to two groups of librarians and IT professionals. Sample was selected by snowball method. Descriptive and inferential statistics were used to analyze the data.
Results: Findings showed that among the databases, Elsevier recommends more relevant results from the perspective of IT professionals and librarians in the field of information storage and retrieval, with Google Scholar and Taylor & Francis in the next ranks. In total, the most relevant articles in terms of subject experts were the articles that ranked fifth.
Conclusion: To sum up, Elsevier performed better than the other two databases in terms of recommending related articles. Also, there is a significant difference between the views of librarians and IT professionals regarding the relevance of recommended articles in the field of information storage and retrieval. Thus, from the point of view of IT professionals, the significance of the recommended articles is greater.
