Finding rising stars in bibliometric networks
Bibliographic Data
| ID | 21442811 |
|---|---|
| Authors | Ali Daud (0000-0002-8284-6354, University of Jeddah, corresponding author), Min Song (0000-0003-3255-1600, Yonsei University), Malik Khizar Hayat (0000-0001-8177-2042, International Islamic University, Islamabad), Tehmina Amjad (0000-0003-1201-498X, International Islamic University, Islamabad), Rabeeh Ayaz Abbasi (0000-0002-3787-7039), Hassan Dawood, Hussain Dawood (0000-0003-2653-9541, University of Engineering and Technology Lahore), Anwar Ghani (0000-0001-7474-0405, International Islamic University, Islamabad) |
| Year | 2020 |
| Volume | 124 |
| Issue | 1 |
| Pages | 633-661 |
| Publication date | 2020-07-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Scientometrics (JOURNAL) |
| Journal identifiers | ISSN: 0138-9130 • E-ISSN: 1588-2861 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s11192-020-03466-w |
| OpenAlex | W3016250837 |
| Language | EN |
| Citations received | 5 |
| References cited | 44 |
Bibliometrics · Cluster analysis · Data science · Economic growth · Economics · Information retrieval · Join (topology) · Productivity · Ranking (information retrieval) · World Wide Web · Advanced Graph Neural Networks · Artificial Intelligence · Complex Network Analysis Techniques · Computer Science · Expert finding and Q&A systems · Mathematics
Identifying Rising Stars via Supervised Machine Learning
Research paper recommendation system based on multiple features from citation network
Predicting the future impact of Computer Science researchers
Features, techniques and evaluation in predicting articles’ citations
Investigating the impact of collaboration with authority authors
| Unique citing works | 5 |
|---|---|
| Citations per year | 1 |
| Citation span | 2021 - 2024 (4) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 5 |