Mohammad Ehsan Basiri

2.7k total citations · 1 hit paper
35 papers, 1.9k citations indexed

About

Mohammad Ehsan Basiri is a scholar working on Artificial Intelligence, Information Systems and Sociology and Political Science. According to data from OpenAlex, Mohammad Ehsan Basiri has authored 35 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Artificial Intelligence, 10 papers in Information Systems and 5 papers in Sociology and Political Science. Recurrent topics in Mohammad Ehsan Basiri's work include Sentiment Analysis and Opinion Mining (21 papers), Advanced Text Analysis Techniques (13 papers) and Topic Modeling (9 papers). Mohammad Ehsan Basiri is often cited by papers focused on Sentiment Analysis and Opinion Mining (21 papers), Advanced Text Analysis Techniques (13 papers) and Topic Modeling (9 papers). Mohammad Ehsan Basiri collaborates with scholars based in Iran, Australia and Canada. Mohammad Ehsan Basiri's co-authors include Shahla Nemati, Moloud Abdar, Nasser Ghasem-Aghaee, Mehdi Hosseinzadeh Aghdam, U. Rajendra Acharya, Erik Cambria, Somayeh Asadi, Ahmad Reza Naghsh‐Nilchi, Mehmet Akif Çifçi and Xujuan Zhou and has published in prestigious journals such as Renewable and Sustainable Energy Reviews, Expert Systems with Applications and IEEE Access.

In The Last Decade

Mohammad Ehsan Basiri

34 papers receiving 1.8k citations

Hit Papers

ABCDM: An Attention-based Bidirectional CNN-RNN Deep Mode... 2020 2026 2022 2024 2020 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mohammad Ehsan Basiri Iran 20 1.4k 302 218 214 115 35 1.9k
Shahla Nemati Iran 12 894 0.6× 159 0.5× 161 0.7× 120 0.6× 61 0.5× 19 1.2k
Lin Li China 22 1.0k 0.7× 428 1.4× 135 0.6× 367 1.7× 42 0.4× 243 2.0k
Katarzyna Musiał Australia 20 738 0.5× 237 0.8× 137 0.6× 159 0.7× 40 0.3× 81 1.5k
Sivaji Bandyopadhyay India 26 2.8k 1.9× 368 1.2× 109 0.5× 479 2.2× 34 0.3× 291 3.4k
Jun Yan China 24 939 0.7× 328 1.1× 117 0.5× 392 1.8× 57 0.5× 81 1.7k
Lei Li China 24 1.0k 0.7× 784 2.6× 180 0.8× 293 1.4× 72 0.6× 237 2.3k
Yan Fu China 19 451 0.3× 262 0.9× 75 0.3× 91 0.4× 99 0.9× 129 1.3k
Ioannis Hatzilygeroudis Greece 21 872 0.6× 343 1.1× 78 0.4× 168 0.8× 70 0.6× 142 1.6k
Liang Yao China 18 1.4k 1.0× 275 0.9× 123 0.6× 243 1.1× 33 0.3× 36 1.9k
A.C.M. Fong New Zealand 22 891 0.6× 640 2.1× 155 0.7× 214 1.0× 159 1.4× 164 2.0k

Countries citing papers authored by Mohammad Ehsan Basiri

Since Specialization
Citations

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

Fields of papers citing papers by Mohammad Ehsan Basiri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohammad Ehsan Basiri. 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 Mohammad Ehsan Basiri. The network helps show where Mohammad Ehsan Basiri may publish in the future.

Co-authorship network of co-authors of Mohammad Ehsan Basiri

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

All Works

20 of 20 papers shown
1.
Derakhshandeh, Sayed Yaser, et al.. (2024). A new hybrid approach for cold load restoration using deep learning. Electric Power Systems Research. 234. 110517–110517. 1 indexed citations
2.
Basiri, Mohammad Ehsan, et al.. (2021). Identifying High-Quality User Replies Using Deep Neural Networks. 97–102. 1 indexed citations
3.
Basiri, Mohammad Ehsan, et al.. (2021). Sentiment Analysis of Persian Instagram Post: a Multimodal Deep Learning Approach. 137–141. 8 indexed citations
4.
Basiri, Mohammad Ehsan, et al.. (2021). A novel fusion-based deep learning model for sentiment analysis of COVID-19 tweets. Knowledge-Based Systems. 228. 107242–107242. 133 indexed citations
5.
Afzal, Muhammad Tanvir, et al.. (2020). A comprehensive analysis of adverb types for mining user sentiments on amazon product reviews. World Wide Web. 23(3). 1811–1829. 35 indexed citations
6.
Basiri, Mohammad Ehsan, et al.. (2020). Review Helpfulness Prediction Using Convolutional Neural Networks and Gated Recurrent Units. 57. 191–196. 6 indexed citations
7.
Basiri, Mohammad Ehsan, et al.. (2020). Bidirectional LSTM Deep Model for Online Doctor Reviews Polarity Detection. 100–105. 4 indexed citations
8.
Abdar, Moloud, Roohallah Alizadehsani, Sadiq Hussain, et al.. (2020). Association between work-related features and coronary artery disease: A heterogeneous hybrid feature selection integrated with balancing approach. Pattern Recognition Letters. 133. 33–40. 80 indexed citations
9.
Abdar, Moloud, Mohammad Ehsan Basiri, Junjun Yin, et al.. (2020). Energy choices in Alaska: Mining people's perception and attitudes from geotagged tweets. Renewable and Sustainable Energy Reviews. 124. 109781–109781. 49 indexed citations
10.
Basiri, Mohammad Ehsan, et al.. (2019). Improving Sentiment Polarity Detection Through Target Identification. IEEE Transactions on Computational Social Systems. 7(1). 113–128. 19 indexed citations
11.
Nemati, Shahla, et al.. (2019). A Hybrid Latent Space Data Fusion Method for Multimodal Emotion Recognition. IEEE Access. 7. 172948–172964. 65 indexed citations
12.
Basiri, Mohammad Ehsan, et al.. (2019). The effect of aggregation methods on sentiment classification in Persian reviews. Enterprise Information Systems. 14(9-10). 1394–1421. 20 indexed citations
13.
Shahid, Abdul, Muhammad Tanvir Afzal, Moloud Abdar, et al.. (2019). Insights into relevant knowledge extraction techniques: a comprehensive review. The Journal of Supercomputing. 76(3). 1695–1733. 19 indexed citations
14.
Tuncer, Türker, Şengül Doğan, Moloud Abdar, Mohammad Ehsan Basiri, & Paweł Pławiak. (2019). Face Recognition with Triangular Fuzzy Set-Based Local Cross Patterns in Wavelet Domain. Symmetry. 11(6). 787–787. 16 indexed citations
16.
Basiri, Mohammad Ehsan, et al.. (2017). Sentence-level sentiment analysis in Persian. 84–89. 29 indexed citations
17.
Basiri, Mohammad Ehsan, et al.. (2014). A Framework for Sentiment Analysis in Persian. 1–14. 31 indexed citations
18.
Basiri, Mohammad Ehsan, Ahmad Reza Naghsh‐Nilchi, & Nasser Ghasem-Aghaee. (2014). Sentiment Prediction Based on Dempster‐Shafer Theory of Evidence. Mathematical Problems in Engineering. 2014(1). 37 indexed citations
19.
Nemati, Shahla, Mohammad Ehsan Basiri, Nasser Ghasem-Aghaee, & Mehdi Hosseinzadeh Aghdam. (2009). A novel ACO–GA hybrid algorithm for feature selection in protein function prediction. Expert Systems with Applications. 36(10). 12086–12094. 159 indexed citations
20.
Aghdam, Mehdi Hosseinzadeh, Nasser Ghasem-Aghaee, & Mohammad Ehsan Basiri. (2008). Text feature selection using ant colony optimization. Expert Systems with Applications. 36(3). 6843–6853. 287 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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