Knowledge graph technology application in Chinese SSCI: An example of short videos research
Thousands of new publications appear every day in bibliometric databases, so the demand for document retrieval technology is growing. Bibliometrics makes it possible to perform a quantitative analysis of text publications; however, the problem of classifying complex videos with a high level of seman...
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Veröffentlicht in: | Journal of librarianship and information science 2023-03, Vol.55 (1), p.84-98 |
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description | Thousands of new publications appear every day in bibliometric databases, so the demand for document retrieval technology is growing. Bibliometrics makes it possible to perform a quantitative analysis of text publications; however, the problem of classifying complex videos with a high level of semantics remains unsolved. Meanwhile, short-form videos gain popularity and attract more researchers. Knowledge Graph seems to be a promising technology in this area. This technology makes it possible to modernize the information search infrastructure. The experiment involved 461 short-video studies. The material for the experiment was collected from the Chinese Social Sciences Citation Index (CSSCI) database. The bibliometric method was recognized as expedient for the analysis. The keyword mapping and clustering operations were performed using the CiteSpace software. The results demonstrate that short-form video research has been popular among Chinese scientists since 2017. Short-form video research focuses on five major topics, that is, development trends, modern media convergence, video production, visual content management, and short-form videos in the public sector. The present findings may be employed in future research to collect relevant samples with exact semantic relationships. The technology is not limited to specific applications and, therefore, may be useful in any field of research. |
doi_str_mv | 10.1177/09610006211063201 |
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Bibliometrics makes it possible to perform a quantitative analysis of text publications; however, the problem of classifying complex videos with a high level of semantics remains unsolved. Meanwhile, short-form videos gain popularity and attract more researchers. Knowledge Graph seems to be a promising technology in this area. This technology makes it possible to modernize the information search infrastructure. The experiment involved 461 short-video studies. The material for the experiment was collected from the Chinese Social Sciences Citation Index (CSSCI) database. The bibliometric method was recognized as expedient for the analysis. The keyword mapping and clustering operations were performed using the CiteSpace software. The results demonstrate that short-form video research has been popular among Chinese scientists since 2017. Short-form video research focuses on five major topics, that is, development trends, modern media convergence, video production, visual content management, and short-form videos in the public sector. The present findings may be employed in future research to collect relevant samples with exact semantic relationships. The technology is not limited to specific applications and, therefore, may be useful in any field of research.</description><identifier>ISSN: 0961-0006</identifier><identifier>EISSN: 1741-6477</identifier><identifier>DOI: 10.1177/09610006211063201</identifier><language>eng</language><publisher>London, England: SAGE Publications</publisher><subject>Bibliometrics ; Graph representations ; Semantics</subject><ispartof>Journal of librarianship and information science, 2023-03, Vol.55 (1), p.84-98</ispartof><rights>The Author(s) 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c312t-191329c222a9a4d46d618413d729818331a0d975687be28760820d49d62147fb3</citedby><cites>FETCH-LOGICAL-c312t-191329c222a9a4d46d618413d729818331a0d975687be28760820d49d62147fb3</cites><orcidid>0000-0002-1077-7337</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/09610006211063201$$EPDF$$P50$$Gsage$$H</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1177/09610006211063201$$EHTML$$P50$$Gsage$$H</linktohtml><link.rule.ids>314,776,780,21798,27901,27902,43597,43598</link.rule.ids></links><search><creatorcontrib>Yang, Wancheng</creatorcontrib><creatorcontrib>Ning, Hailin</creatorcontrib><title>Knowledge graph technology application in Chinese SSCI: An example of short videos research</title><title>Journal of librarianship and information science</title><description>Thousands of new publications appear every day in bibliometric databases, so the demand for document retrieval technology is growing. Bibliometrics makes it possible to perform a quantitative analysis of text publications; however, the problem of classifying complex videos with a high level of semantics remains unsolved. Meanwhile, short-form videos gain popularity and attract more researchers. Knowledge Graph seems to be a promising technology in this area. This technology makes it possible to modernize the information search infrastructure. The experiment involved 461 short-video studies. The material for the experiment was collected from the Chinese Social Sciences Citation Index (CSSCI) database. The bibliometric method was recognized as expedient for the analysis. The keyword mapping and clustering operations were performed using the CiteSpace software. The results demonstrate that short-form video research has been popular among Chinese scientists since 2017. Short-form video research focuses on five major topics, that is, development trends, modern media convergence, video production, visual content management, and short-form videos in the public sector. The present findings may be employed in future research to collect relevant samples with exact semantic relationships. 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Bibliometrics makes it possible to perform a quantitative analysis of text publications; however, the problem of classifying complex videos with a high level of semantics remains unsolved. Meanwhile, short-form videos gain popularity and attract more researchers. Knowledge Graph seems to be a promising technology in this area. This technology makes it possible to modernize the information search infrastructure. The experiment involved 461 short-video studies. The material for the experiment was collected from the Chinese Social Sciences Citation Index (CSSCI) database. The bibliometric method was recognized as expedient for the analysis. The keyword mapping and clustering operations were performed using the CiteSpace software. The results demonstrate that short-form video research has been popular among Chinese scientists since 2017. Short-form video research focuses on five major topics, that is, development trends, modern media convergence, video production, visual content management, and short-form videos in the public sector. The present findings may be employed in future research to collect relevant samples with exact semantic relationships. The technology is not limited to specific applications and, therefore, may be useful in any field of research.</abstract><cop>London, England</cop><pub>SAGE Publications</pub><doi>10.1177/09610006211063201</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-1077-7337</orcidid></addata></record> |
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subjects | Bibliometrics Graph representations Semantics |
title | Knowledge graph technology application in Chinese SSCI: An example of short videos research |
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