Saidah Saad

59 total papers · 624 total citations
48 papers, 381 citations indexed

About

Saidah Saad is a scholar working on Artificial Intelligence, Information Systems and Education. According to data from OpenAlex, Saidah Saad has authored 48 papers receiving a total of 381 indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Artificial Intelligence, 18 papers in Information Systems and 5 papers in Education. Recurrent topics in Saidah Saad's work include Topic Modeling (17 papers), Advanced Text Analysis Techniques (15 papers) and Semantic Web and Ontologies (14 papers). Saidah Saad is often cited by papers focused on Topic Modeling (17 papers), Advanced Text Analysis Techniques (15 papers) and Semantic Web and Ontologies (14 papers). Saidah Saad collaborates with scholars based in Malaysia, China and Indonesia. Saidah Saad's co-authors include Naomie Salim, Shahrul Azman Mohd Noah, Sabrina Tiun, Nazlia Omar, Umi Asma’ Mokhtar, Ramli Musa, Harith Alani, Mohd Zain, Mohamed Hussein and Jingming Hou and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Neural Networks.

In The Last Decade

Saidah Saad

41 papers receiving 355 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Saidah Saad	260	139	39	34	33	48	381
Jeroen Keppens	220 0.8×	65 0.5×	42 1.1×	22 0.6×	50 1.5×	44	403
Daniel McDonald	162 0.6×	138 1.0×	44 1.1×	31 0.9×	23 0.7×	26	342
Moch Arif Bijaksana	293 1.1×	167 1.2×	34 0.9×	23 0.7×	28 0.8×	86	417
G Veena	203 0.8×	74 0.5×	29 0.7×	35 1.0×	16 0.5×	32	397
Clare Beghtol	143 0.6×	136 1.0×	68 1.7×	15 0.4×	18 0.5×	25	402
Ingetraut Dahlberg	187 0.7×	151 1.1×	41 1.1×	11 0.3×	22 0.7×	28	373
Esther Kaufmann	195 0.8×	69 0.5×	22 0.6×	37 1.1×	48 1.5×	22	362
Koraljka Golub	230 0.9×	206 1.5×	20 0.5×	10 0.3×	40 1.2×	77	400
Ying‐Hsang Liu	130 0.5×	148 1.1×	95 2.4×	17 0.5×	19 0.6×	57	444
Gregory H. Leazer	111 0.4×	197 1.4×	37 0.9×	24 0.7×	20 0.6×	31	412

Countries citing papers authored by Saidah Saad

Since Specialization

Citations

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

Fields of papers citing papers by Saidah Saad

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Saidah Saad. 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 Saidah Saad. The network helps show where Saidah Saad may publish in the future.

Co-authorship network of co-authors of Saidah Saad

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

All Works

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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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