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My bibliography Save this articleUnderstanding the topic evolution in a scientific domain: An exploratory study for the field of information retrieval
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DOI: 10.1016/j.joi.2017.10.003
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Cited by:
- Chen, Hongshu & Jin, Qianqian & Wang, Ximeng & Xiong, Fei, 2022. "Profiling academic-industrial collaborations in bibliometric-enhanced topic networks: A case study on digitalization research," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
- Yating Li & Ye Chen & Qiyu Wang, 2021. "Evolution and diffusion of information literacy topics," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4195-4224, May.
- Jian Xu & Yi Bu & Ying Ding & Sinan Yang & Hongli Zhang & Chen Yu & Lin Sun, 2018. "Understanding the formation of interdisciplinary research from the perspective of keyword evolution: a case study on joint attention," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 973-995, November.
- David Doloreux & Jose Gaviria de la Puerta & Iker Pastor-López & Igone Porto Gómez & Borja Sanz & Jon Mikel Zabala-Iturriagagoitia, 2019. "Territorial innovation models: to be or not to be, that’s the question," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(3), pages 1163-1191, September.
- Lukun Zheng & Yuhang Jiang, 2022. "Combining dissimilarity measures for quantifying changes in research fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 3751-3765, July.
- Jung, Sukhwan & Yoon, Wan Chul, 2020. "An alternative topic model based on Common Interest Authors for topic evolution analysis," Journal of Informetrics, Elsevier, vol. 14(3).
- WATANABE Ichiro & SHIMIZU Hiroshi, 2024. "Mainstream Formation and Competitive Dynamics in the Computer Graphics Industry: Topic modeling analysis of US patents," Discussion papers 24018, Research Institute of Economy, Trade and Industry (RIETI).
- Jung, Sukhwan & Segev, Aviv, 2022. "DAC: Descendant-aware clustering algorithm for network-based topic emergence prediction," Journal of Informetrics, Elsevier, vol. 16(3).
- Chaker Jebari & Enrique Herrera-Viedma & Manuel Jesus Cobo, 2021. "The use of citation context to detect the evolution of research topics: a large-scale analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 2971-2989, April.
- Lu Huang & Xiang Chen & Yi Zhang & Changtian Wang & Xiaoli Cao & Jiarun Liu, 2022. "Identification of topic evolution: network analytics with piecewise linear representation and word embedding," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5353-5383, September.
- Zhentao Liang & Jin Mao & Kun Lu & Gang Li, 2021. "Finding citations for PubMed: a large-scale comparison between five freely available bibliographic data sources," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(12), pages 9519-9542, December.
- Huichen Gao & Shijuan Wang, 2022. "The Intellectual Structure of Research on Rural-to-Urban Migrants: A Bibliometric Analysis," IJERPH, MDPI, vol. 19(15), pages 1-19, August.
- Yosuke Miyata & Emi Ishita & Fang Yang & Michimasa Yamamoto & Azusa Iwase & Keiko Kurata, 2020. "Knowledge structure transition in library and information science: topic modeling and visualization," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 665-687, October.
- David Chavalarias & Quentin Lobbé & Alexandre Delanoë, 2022. "Draw me Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 545-575, January.
- Wang, Xiaoguang & He, Jing & Huang, Han & Wang, Hongyu, 2022. "MatrixSim: A new method for detecting the evolution paths of research topics," Journal of Informetrics, Elsevier, vol. 16(4).
- Xu, Shuo & Hao, Liyuan & An, Xin & Yang, Guancan & Wang, Feifei, 2019. "Emerging research topics detection with multiple machine learning models," Journal of Informetrics, Elsevier, vol. 13(4).
- Baitong Chen & Ying Ding & Feicheng Ma, 2018. "Semantic word shifts in a scientific domain," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 211-226, October.
- Seyyed Reza Taher Harikandeh & Sadegh Aliakbary & Soroush Taheri, 2023. "An embedding approach for analyzing the evolution of research topics with a case study on computer science subdomains," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1567-1582, March.
- Mauricio Marrone, 2020. "Application of entity linking to identify research fronts and trends," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 357-379, January.
- Huixin Wang & Jing Xie & Shixian Luo & Duy Thong Ta & Qian Wang & Jiao Zhang & Daer Su & Katsunori Furuya, 2023. "Exploring the Interplay between Landscape Planning and Human Well-Being: A Scientometric Review," Land, MDPI, vol. 12(7), pages 1-24, June.
- Hengmin Zhu & Li Qian & Wang Qin & Jing Wei & Chao Shen, 2022. "Evolution analysis of online topics based on ‘word-topic’ coupling network," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 3767-3792, July.
- Jian Xu & Ying Ding & Yi Bu & Shuqing Deng & Chen Yu & Yimin Zou & Andrew Madden, 2019. "Interdisciplinary scholarly communication: an exploratory study for the field of joint attention," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1597-1619, June.
- Qiang Gao & Xiao Huang & Ke Dong & Zhentao Liang & Jiang Wu, 2022. "Semantic-enhanced topic evolution analysis: a combination of the dynamic topic model and word2vec," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(3), pages 1543-1563, March.
- Qian, Yue & Liu, Yu & Sheng, Quan Z., 2020. "Understanding hierarchical structural evolution in a scientific discipline: A case study of artificial intelligence," Journal of Informetrics, Elsevier, vol. 14(3).
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Keywords
Topic evolution; Semantic word shifts; Content analysis;All these keywords.
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