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| Research on Information Cocoon Identification and Cocoon Breaking Topic Recommendation in Research Collaboration Groups |
| Chen Xiang1, Huang Lu2,3, Cao Xiaoli4, Ren Hang5 |
1.School of Management, Beijing Institute of Technology, Beijing 100081
2.School of Economics, Beijing Institute of Technology, Beijing 100081
3.Digital Economy and Policy Intelligentization Key Laboratory of Ministry of Industry and Information Technology, Beijing 100081
4.China Agricultural University Library, Beijing 100193
5.Beijing Institute of Technology, Zhuhai 519088 |
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Abstract As collaborative relationships among researchers become increasingly entrenched, the emergence of information cocoons within scientific collaboration groups may hinder interdisciplinary integration and limit advancements in collaborative scientific innovation. This paper proposes a method for identifying information cocoons and recommending breakthrough research topics in scientific collaboration groups. First, a time-series, two-layer network comprising co-authorship and keyword semantic similarity was constructed. An incremental community detection algorithm is applied to extract the evolving community structure in the cumulative co-authorship network over time. Each author’s research topic vector was calculated based on the correspondence between the authors and keywords across a two-layer network. Information cocoons are identified by jointly considering topic homogeneity and novelty metrics. Second, an information dissemination influence measurement model is constructed to measure the potential of author nodes to break out of a cocoon. Then, a co-authorship - keyword semantic two-layer network considering the ranking of potential to break out of the cocoon is generated, and an author topic recommendation algorithm based on restarted random walk (ATR_RWR) is proposed to help researchers break out of the cocoon. An empirical analysis was conducted in the field of computer science to validate the effectiveness of the proposed method.
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Received: 03 June 2025
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