Ally S. Nyamawe

436 total citations
27 papers, 264 citations indexed

About

Ally S. Nyamawe is a scholar working on Information Systems, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Ally S. Nyamawe has authored 27 papers receiving a total of 264 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Information Systems, 8 papers in Artificial Intelligence and 7 papers in Computer Networks and Communications. Recurrent topics in Ally S. Nyamawe's work include Software Engineering Research (8 papers), Spam and Phishing Detection (6 papers) and Misinformation and Its Impacts (6 papers). Ally S. Nyamawe is often cited by papers focused on Software Engineering Research (8 papers), Spam and Phishing Detection (6 papers) and Misinformation and Its Impacts (6 papers). Ally S. Nyamawe collaborates with scholars based in Tanzania, China and United States. Ally S. Nyamawe's co-authors include Zhendong Niu, Hui Liu, Guangjie Li, Nan Niu, Qasim Umer, Zahid Khan, Wentao Wang, Harry Budi Santoso, Abdallah Yousif and Noe Elisa and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.

In The Last Decade

Ally S. Nyamawe

25 papers receiving 248 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Ally S. Nyamawe Tanzania	10	158	82	66	63	43	27	264
Tam The Nguyen United States	9	253 1.6×	74 0.9×	57 0.9×	59 0.9×	73 1.7×	17	317
Humberto T. Marques-Neto Brazil	10	124 0.8×	76 0.9×	77 1.2×	46 0.7×	26 0.6×	50	282
Yudistira Asnar Indonesia	9	187 1.2×	105 1.3×	52 0.8×	52 0.8×	52 1.2×	44	257
Yogesh Deshpande Australia	9	204 1.3×	43 0.5×	34 0.5×	30 0.5×	16 0.4×	32	290
Andreas Biørn-Hansen Norway	7	153 1.0×	41 0.5×	51 0.8×	15 0.2×	24 0.6×	13	236
Phil Greenwood United Kingdom	11	173 1.1×	157 1.9×	92 1.4×	31 0.5×	13 0.3×	28	283
Jichuan Zeng Hong Kong	10	259 1.6×	256 3.1×	46 0.7×	31 0.5×	48 1.1×	15	436
Safwat Hassan Canada	10	194 1.2×	60 0.7×	62 0.9×	37 0.6×	59 1.4×	25	315
Gül Çalıklı United Kingdom	11	297 1.9×	76 0.9×	55 0.8×	133 2.1×	45 1.0×	35	372
Daniel Votipka United States	11	239 1.5×	83 1.0×	82 1.2×	66 1.0×	205 4.8×	24	353

Countries citing papers authored by Ally S. Nyamawe

Since Specialization

Citations

This map shows the geographic impact of Ally S. Nyamawe'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 Ally S. Nyamawe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ally S. Nyamawe more than expected).

Fields of papers citing papers by Ally S. Nyamawe

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ally S. Nyamawe. 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 Ally S. Nyamawe. The network helps show where Ally S. Nyamawe may publish in the future.

Co-authorship network of co-authors of Ally S. Nyamawe

This figure shows the co-authorship network connecting the top 25 collaborators of Ally S. Nyamawe. A scholar is included among the top collaborators of Ally S. Nyamawe 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 Ally S. Nyamawe. Ally S. Nyamawe is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Nyamawe, Ally S., et al.. (2025). LLM-guided fuzzy kinematic modeling for resolving kinematic uncertainties and linguistic ambiguities in text-to-motion generation. Expert Systems with Applications. 279. 127283–127283. 2 indexed citations

Niu, Zhendong, et al.. (2025). Aspect-level sentiment-aware mining of inter-review relations for detecting fake reviews. Knowledge-Based Systems. 329. 114360–114360.

Sensuse, Dana Indra, et al.. (2025). E-SATNet: Evaluating Student Satisfaction with Lecturer Responses in Asynchronous Online Discussions Using Sentiment and Semantic Similarity Analysis. Big Data and Cognitive Computing. 9(9). 228–228.

Niu, Zhendong, et al.. (2025). An analysis of graph neural networks for fake review detection: A systematic literature review. Neurocomputing. 623. 129341–129341. 2 indexed citations

Niu, Zhendong, et al.. (2024). A deep feature interaction and fusion model for fake review detection: Advocating heterogeneous graph convolutional network. Neurocomputing. 598. 128097–128097. 4 indexed citations

Niu, Zhendong, et al.. (2024). SES-Net: A Novel Multi-Task Deep Neural Network Model for Analyzing E-learning Users’ Satisfaction via Sentiment, Emotion, and Semantic. International Journal of Human-Computer Interaction. 41(8). 4910–4933. 3 indexed citations

Niu, Zhendong, et al.. (2024). Fake review detection techniques, issues, and future research directions: a literature review. Knowledge and Information Systems. 66(9). 5071–5112. 9 indexed citations

Nyamawe, Ally S.. (2023). Research on mining software repositories to facilitate refactoring. Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery. 13(5). 2 indexed citations

Niu, Zhendong, et al.. (2023). A Deep Hybrid Model for fake review detection by jointly leveraging review text, overall ratings, and aspect ratings. Soft Computing. 27(10). 6281–6296. 19 indexed citations

10.

Niu, Zhendong, et al.. (2023). DHMFRD – TER: a deep hybrid model for fake review detection incorporating review texts, emotions, and ratings. Multimedia Tools and Applications. 83(2). 4533–4549. 8 indexed citations

11.

Nyamawe, Ally S., et al.. (2023). Exploring the status of artificial intelligence for healthcare research in Africa: a bibliometric and thematic analysis. AI and Ethics. 5(1). 117–138. 2 indexed citations

12.

Nyamawe, Ally S.. (2022). Mining commit messages to enhance software refactorings recommendation: A machine learning approach. SHILAP Revista de lepidopterología. 9. 100316–100316. 12 indexed citations

13.

Nyamawe, Ally S., et al.. (2021). Identifying rename refactoring opportunities based on feature requests. International Journal of Computers and Applications. 44(8). 770–778. 3 indexed citations

14.

Nyamawe, Ally S., Hui Liu, Nan Niu, Qasim Umer, & Zhendong Niu. (2020). Feature requests-based recommendation of software refactorings. Empirical Software Engineering. 25(5). 4315–4347. 22 indexed citations

15.

Nyamawe, Ally S., Hui Liu, Nan Niu, Qasim Umer, & Zhendong Niu. (2019). Automated Recommendation of Software Refactorings Based on Feature Requests. 187–198. 20 indexed citations

16.

Niu, Zhendong, et al.. (2018). A New Scheme for Citation Classification based on Convolutional Neural Networks. Proceedings/Proceedings of the ... International Conference on Software Engineering and Knowledge Engineering. 2018. 131–168. 6 indexed citations

17.

Nyamawe, Ally S., Hui Liu, Zhendong Niu, Wentao Wang, & Nan Niu. (2018). Recommending Refactoring Solutions Based on Traceability and Code Metrics. IEEE Access. 6. 49460–49475. 22 indexed citations

18.

Nyamawe, Ally S., et al.. (2014). Road Safety: Adoption of ICT for Tracking Vehicles' Over-speeding in Tanzania. International Journal of Computer Applications. 96(16). 12–15. 4 indexed citations

19.

Nyamawe, Ally S., et al.. (2014). The Use of Mobile Phones in University Exams Cheating: Proposed Solution. International Journal of Engineering Trends and Technology. 17(1). 14–17. 11 indexed citations

20.

Nyamawe, Ally S., et al.. (2014). The Role of ICT in Reducing Maternal and Neonatal Mortality Rate in Tanzania. International Journal of Computer Applications. 95(13). 39–42. 10 indexed citations

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.

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