Renu Balyan
About
In The Last Decade
Renu Balyan
22 papers receiving 191 citations
Peers
Comparison fields: 5 of 72
- Artificial Intelligence 93
- General Health Professions 65
- Developmental and Educational Psychology 24
- Oncology 16
- Health 14
Countries citing papers authored by Renu Balyan
This map shows the geographic impact of Renu Balyan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Renu Balyan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Renu Balyan more than expected).
Fields of papers citing papers by Renu Balyan
This network shows the impact of papers produced by Renu Balyan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Renu Balyan. The network helps show where Renu Balyan may publish in the future.
Co-authorship network of co-authors of Renu Balyan
This figure shows the co-authorship network connecting the top 25 collaborators of Renu Balyan. A scholar is included among the top collaborators of Renu Balyan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Renu Balyan. Renu Balyan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 6 | |
| 5 | 1 | |
| 6 | 3 | |
| 7 | 1 | |
| 8 | 27 | |
| 9 | Linguistic Features of Discourse within an Algebra Online Discussion Board | 1 |
| 10 | 3 | |
| 11 | 10 | |
| 12 | 33 | |
| 13 | 10 | |
| 14 | 10 | |
| 15 | 22 | |
| 16 | 9 | |
| 17 | Comparing Machine Learning Classification Approaches for Predicting Expository Text Difficulty. | 7 |
| 18 | Combining Machine Learning and Natural Language Processing to Assess Literary Text Comprehension. | 4 |
| 19 | Context Resolution of Verb Particle Constructions for English to Hindi Translation | 2 |
| 20 | A step towards Human-Machine unification using Translation Memory and Machine Translation System | 2 |
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.