Sarah Alhumoud

15 papers and 169 indexed citations i.

About

Sarah Alhumoud is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Sarah Alhumoud has authored 15 papers receiving a total of 169 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 3 papers in Information Systems and 2 papers in Computer Networks and Communications. Recurrent topics in Sarah Alhumoud’s work include Sentiment Analysis and Opinion Mining (6 papers), Advanced Text Analysis Techniques (5 papers) and Topic Modeling (5 papers). Sarah Alhumoud is often cited by papers focused on Sentiment Analysis and Opinion Mining (6 papers), Advanced Text Analysis Techniques (5 papers) and Topic Modeling (5 papers). Sarah Alhumoud collaborates with scholars based in Saudi Arabia, United Kingdom and United States. Sarah Alhumoud's co-authors include Muna Al‐Razgan, Hend S. Al‐Khalifa, Alexandra I. Cristea, Lewis Mackenzie, Nora Al-Twairesh and M. Ould‐Khaoua and has published in prestigious journals such as IEEE Access, Artificial Intelligence Review and Lecture notes in computer science.

In The Last Decade

Co-authorship network of co-authors of Sarah Alhumoud i

Fields of papers citing papers by Sarah Alhumoud

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Sarah Alhumoud

Since Specialization
Citations

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

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2025