Interdisciplinary topics of information science: a study based on the terms interdisciplinarity index series
Abstract Interdisciplinarity is increasingly widespread. Many technological frontiers and hotspots are emerging in the intersecting research areas. The existing measurement indexes of interdisciplinarity are mostly based on the co-occurrence of authors, institutions, or references, and most focus on...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Xu, Haiyun [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Schlagwörter: |
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| Anmerkung: |
© Akadémiai Kiadó, Budapest, Hungary 2016 |
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| Übergeordnetes Werk: |
Enthalten in: Scientometrics - Springer Netherlands, 1978, 106(2016), 2 vom: 05. Jan., Seite 583-601 |
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| Übergeordnetes Werk: |
volume:106 ; year:2016 ; number:2 ; day:05 ; month:01 ; pages:583-601 |
| Links: |
|---|
| DOI / URN: |
10.1007/s11192-015-1792-2 |
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OLC2033209466 |
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| 520 | |a Abstract Interdisciplinarity is increasingly widespread. Many technological frontiers and hotspots are emerging in the intersecting research areas. The existing measurement indexes of interdisciplinarity are mostly based on the co-occurrence of authors, institutions, or references, and most focus on the tendency to interdisciplinarity. This paper introduces a new measurement index entitled topic terms interdisciplinarity (TI) for interdisciplinarity topic mining. Taking Information Science & Library Science (LIS) as a case study, this paper identifies interdisciplinary topics by calculating TI values together with Bet values, term frequency values, and others, and analyzes the evolution of interdisciplinary sciences based on social network analysis and time series analysis. It was found that the intersections of external disciplines and pivots of internal topics for LIS can be identified by the utilization of TI value and Bet values. The research has shown that the TI value can identify interdisciplinary topic terms well, and it will be an efficient indicator for interdisciplinary analysis by being complementary to other methods. | ||
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Interdisciplinary topics of information science: a study based on the terms interdisciplinarity index series |
| abstract |
Abstract Interdisciplinarity is increasingly widespread. Many technological frontiers and hotspots are emerging in the intersecting research areas. The existing measurement indexes of interdisciplinarity are mostly based on the co-occurrence of authors, institutions, or references, and most focus on the tendency to interdisciplinarity. This paper introduces a new measurement index entitled topic terms interdisciplinarity (TI) for interdisciplinarity topic mining. Taking Information Science & Library Science (LIS) as a case study, this paper identifies interdisciplinary topics by calculating TI values together with Bet values, term frequency values, and others, and analyzes the evolution of interdisciplinary sciences based on social network analysis and time series analysis. It was found that the intersections of external disciplines and pivots of internal topics for LIS can be identified by the utilization of TI value and Bet values. The research has shown that the TI value can identify interdisciplinary topic terms well, and it will be an efficient indicator for interdisciplinary analysis by being complementary to other methods. © Akadémiai Kiadó, Budapest, Hungary 2016 |
| abstractGer |
Abstract Interdisciplinarity is increasingly widespread. Many technological frontiers and hotspots are emerging in the intersecting research areas. The existing measurement indexes of interdisciplinarity are mostly based on the co-occurrence of authors, institutions, or references, and most focus on the tendency to interdisciplinarity. This paper introduces a new measurement index entitled topic terms interdisciplinarity (TI) for interdisciplinarity topic mining. Taking Information Science & Library Science (LIS) as a case study, this paper identifies interdisciplinary topics by calculating TI values together with Bet values, term frequency values, and others, and analyzes the evolution of interdisciplinary sciences based on social network analysis and time series analysis. It was found that the intersections of external disciplines and pivots of internal topics for LIS can be identified by the utilization of TI value and Bet values. The research has shown that the TI value can identify interdisciplinary topic terms well, and it will be an efficient indicator for interdisciplinary analysis by being complementary to other methods. © Akadémiai Kiadó, Budapest, Hungary 2016 |
| abstract_unstemmed |
Abstract Interdisciplinarity is increasingly widespread. Many technological frontiers and hotspots are emerging in the intersecting research areas. The existing measurement indexes of interdisciplinarity are mostly based on the co-occurrence of authors, institutions, or references, and most focus on the tendency to interdisciplinarity. This paper introduces a new measurement index entitled topic terms interdisciplinarity (TI) for interdisciplinarity topic mining. Taking Information Science & Library Science (LIS) as a case study, this paper identifies interdisciplinary topics by calculating TI values together with Bet values, term frequency values, and others, and analyzes the evolution of interdisciplinary sciences based on social network analysis and time series analysis. It was found that the intersections of external disciplines and pivots of internal topics for LIS can be identified by the utilization of TI value and Bet values. The research has shown that the TI value can identify interdisciplinary topic terms well, and it will be an efficient indicator for interdisciplinary analysis by being complementary to other methods. © Akadémiai Kiadó, Budapest, Hungary 2016 |
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| title_short |
Interdisciplinary topics of information science: a study based on the terms interdisciplinarity index series |
| url |
https://doi.org/10.1007/s11192-015-1792-2 |
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false |
| author2 |
Guo, Ting Yue, Zenghui Ru, Lijie Fang, Shu |
| author2Str |
Guo, Ting Yue, Zenghui Ru, Lijie Fang, Shu |
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| doi_str |
10.1007/s11192-015-1792-2 |
| up_date |
2024-07-03T16:08:34.669Z |
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