Imran Ashraf

359 papers receiving 6.4k citations

Imran Ashraf's Hit Papers

Sentiment Analysis and Topic Modeling on Tweets about Online Education during COVID-19 2021 · 150 citations
1500+1+3Years since publication50100150

Peers

Imran Ashraf
Comparison fields: 5 of 197
  • Health Informatics 102
  • Health Information Management 339
  • Artificial Intelligence 1.9k
  • Computer Networks and Communications 1.0k
  • Information Systems 793
Replace Mehedi Masud with:
Mehedi Masud Saudi Arabia
Simon Fong Macao
Gunasekaran Manogaran United States
Sweta Bhattacharya India
Celestine Iwendi United Kingdom
Anand Nayyar Vietnam
Muhammad Adnan Khan Pakistan
Chinmay Chakraborty India
Sungyoung Lee South Korea
Ketan Kotecha India
Imran Ashraf relative to Mehedi Masud Saudi Arabia Mehedi Masud's profile →
Citations per field
00.5×3.6×
Mehedi Masud · 1×
Citations per year

Countries citing papers authored by Imran Ashraf

Since Specialization
Citations

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

Fields of papers citing papers by Imran Ashraf

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Imran Ashraf, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Imran Ashraf Line = papers co-authored together Imran Ashraf links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 378 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011275
2
Sentiment Analysis and Topic Modeling on Tweets about Online Education during COVID-19
Hit paper breakdown →
2021150
3 2021135
4 2019126
5 2010104
6 202298
7
Garlic (Allium sativum) supplementation with standard antidiabetic agent provides better diabetic control in type 2 diabetes patients.
201197
8 202293
9 202285
10 202282
11 202180
12 202276
13 202272
14 202371
15 202066
16 202066
17 201064
18 201963
19 202261
20 201059

About Imran Ashraf

Imran Ashraf is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Electrical and Electronic Engineering and Radiology, Nuclear Medicine and Imaging, having authored 378 papers that have together received 6.7k indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (40 papers), COVID-19 diagnosis using AI (25 papers), Spam and Phishing Detection (24 papers), Indoor and Outdoor Localization Technologies (23 papers), Artificial Intelligence in Healthcare (21 papers), IoT and Edge/Fog Computing (20 papers), Imbalanced Data Classification Techniques (19 papers) and Network Security and Intrusion Detection (18 papers). The work is most often cited by research in Health Informatics (102 citations), Health Information Management (339 citations), Artificial Intelligence (1.9k citations), Computer Networks and Communications (1.0k citations) and Information Systems (793 citations). Imran Ashraf has collaborated with scholars based in South Korea, Pakistan and Spain. Frequent co-authors include Furqan Rustam, Lester Ho, Soojung Hur, Yongwan Park, Isabel de la Torre Díez, Gyu Sang Choi, Arif Mehmood, Muhammad Umer, Federico Boccardi and Ernesto Lee. Their work appears in journals such as IEEE Access, Sensors, PeerJ Computer Science, Scientific Reports and Multimedia Tools and Applications.

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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