Emaad Manzoor

673 citations
10 papers · 386 indexed · 1 hit paper · h-index 7
Topics
Topic Modeling (4 papers)Sentiment Analysis and Opinion Mining (3 papers)Computational and Text Analysis Methods (2 papers)

In The Last Decade

Emaad Manzoor

10 papers receiving 370 citations

Hit Papers

Causal Inference in Natural Language Processing: Estimati...202220262023202420224080120

Peers

Emaad Manzoor
Comparison fields: 5 of 57
  • Artificial Intelligence 275
  • Computer Networks and Communications 132
  • Information Systems 84
  • Signal Processing 77
  • Computer Vision and Pattern Recognition 31
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Renato Fileto Brazil
Changxuan Wan China
Jagdev Bhogal United Kingdom
Sumit Negi India
Thanh Tran Germany
Tiziano Fagni Italy
Lyndon Nixon Austria
Christian Kohlschütter Germany
Florence Sèdes France
Mário Antunes Portugal
Emaad Manzoor relative to Renato Fileto Brazil Renato Fileto's profile →
Citations per field
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Citations per year

Countries citing papers authored by Emaad Manzoor

Since Specialization
Citations

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

Fields of papers citing papers by Emaad Manzoor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Emaad Manzoor

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

All Works

10 of 10 papers shown
#WorkIndexed citations
1 2
2
Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyondbreakdown →
120
3 18
4 14
5 1
6 17
7 4
8 47
9 9
10 154

About Emaad Manzoor

Emaad Manzoor is a scholar working on General Social Sciences, Artificial Intelligence and Statistics and Probability, having authored 10 papers that have together received 386 indexed citations. Recurring topics across this work include Topic Modeling (4 papers), Sentiment Analysis and Opinion Mining (3 papers) and Computational and Text Analysis Methods (2 papers). The work is most often cited by research in Artificial Intelligence (275 citations), Signal Processing (77 citations) and Computer Networks and Communications (132 citations). Emaad Manzoor has collaborated with scholars based in United States, Canada and Israel. Frequent co-authors include Leman Akoglu, Sadegh M. Milajerdi, Hemank Lamba, Nihar B. Shah, Amir Feder, Reid Pryzant, Dhanya Sridhar, Margaret E. Roberts, Katherine A. Keith and Brandon Stewart. Their work appears in journals such as Information Systems Research, Transactions of the Association for Computational Linguistics and arXiv (Cornell University).

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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