World's Best Scientists 2026 revealed!
Award Badge
Computer Science
Mexico
2026

D-Index & Metrics

Computer Science

D-Index
56
Citations
16392
World Ranking
3998
National Ranking
4

Research.com Recognitions

  • 2026 - Research.com Computer Science in Mexico Leader Award

Overview

Alexander Gelbukh is affiliated with the Instituto Politécnico Nacional in Mexico and has contributed extensively to the field of Computer Science, with a particular focus on Artificial Intelligence. Their research outputs include significant work in Natural Language Processing and related subfields, reflecting an emphasis on text analysis and computational methods for understanding language.

Their scholarly activity covers a range of topics including Topic Modeling, Natural Language Processing Techniques, Sentiment Analysis and Opinion Mining, Advanced Text Analysis Techniques, Hate Speech and Cyberbullying Detection, Misinformation and Its Impacts, and Spam and Phishing Detection.

Alexander Gelbukh has published research in the following key venues:

  • arXiv (Cornell University)
  • Computación y Sistemas
  • Journal of Intelligent & Fuzzy Systems
  • SSRN Electronic Journal
  • Expert Systems with Applications

Selected recent papers authored or co-authored by Gelbukh include:

  • Multi-label emotion classification in texts using transfer learning, 2022, Expert Systems with Applications
  • Urdu Sentiment Analysis With Deep Learning Methods, 2021, IEEE Access
  • "Bend the truth": Benchmark dataset for fake news detection in Urdu language and its evaluation, 2020, Journal of Intelligent & Fuzzy Systems
  • Threatening Language Detection and Target Identification in Urdu Tweets, 2021, IEEE Access
  • Abusive language detection in youtube comments leveraging replies as conversational context, 2021, PeerJ Computer Science

The scientist has collaborated frequently with other researchers including Grigori Sidorov, Olga Kolesnikova, Sabur Butt, Maaz Amjad, and Fazlourrahman Balouchzahi, with multiple joint publications reflecting an ongoing network of productive research partnerships.

In addition to journal articles, Alexander Gelbukh has contributed to book publications primarily through Springer Science+Business Media. These publications include multiple editions of Computational Linguistics and Intelligent Text Processing released in 2023, as well as Advances in Soft Computing and Advances in Computational Intelligence, both published in 2021.

Best Publications

  • Computational Linguistics and Intelligent Text Processing

    Alexander F. Gelbukh

  • Aspect extraction for opinion mining with a deep convolutional neural network

    Soujanya Poria;Erik Cambria;Alexander Gelbukh

  • DialogueRNN: An Attentive RNN for Emotion Detection in Conversations.

    Navonil Majumder;Soujanya Poria;Devamanyu Hazarika;Rada Mihalcea

  • Deep Learning-Based Document Modeling for Personality Detection from Text

    Navonil Majumder;Soujanya Poria;Alexander Gelbukh;Erik Cambria

  • Deep Convolutional Neural Network Textual Features and Multiple Kernel Learning for Utterance-level Multimodal Sentiment Analysis

    Soujanya Poria;Erik Cambria;Alexander Gelbukh

  • DialogueGCN: A graph convolutional neural network for emotion recognition in conversation

    Deepanway Ghosal;Navonil Majumder;Soujanya Poria;Niyati Chhaya

  • Soft Similarity and Soft Cosine Measure: Similarity of Features in Vector Space Model

    Grigori Sidorov;Alexander F. Gelbukh;Helena Gómez-Adorno;David Pinto

  • Sentiment Analysis Is a Big Suitcase

    Erik Cambria;Soujanya Poria;Alexander Gelbukh;Mike Thelwall

  • Syntactic N-grams as machine learning features for natural language processing

    Grigori Sidorov;Francisco Velasquez;Efstathios Stamatatos;Alexander Gelbukh

  • Multimodal sentiment analysis using hierarchical fusion with context modeling

    Navonil Majumder;Devamanyu Hazarika;Alexander F. Gelbukh;Erik Cambria

  • A Rule-Based Approach to Aspect Extraction from Product Reviews

    Soujanya Poria;Erik Cambria;Lun-Wei Ku;Chen Gui

  • Multilingual Sentiment Analysis: State of the Art and Independent Comparison of Techniques.

    Kia Dashtipour;Soujanya Poria;Amir Hussain;Erik Cambria

  • Recent trends in deep learning based personality detection

    Yash Mehta;Navonil Majumder;Alexander F. Gelbukh;Erik Cambria

  • Enhanced SenticNet with Affective Labels for Concept-Based Opinion Mining

    S. Poria;A. Gelbukh;A. Hussain;N. Howard

  • COSMIC: COmmonSense knowledge for eMotion Identification in Conversations

    Deepanway Ghosal;Navonil Majumder;Alexander F. Gelbukh;Rada Mihalcea

  • Sentiment and Sarcasm Classification With Multitask Learning

    Navonil Majumder;Soujanya Poria;Haiyun Peng;Niyati Chhaya

  • EmoSenticSpace: a novel framework for affective common-sense reasoning

    Soujanya Poria;Alexander Gelbukh;Erik Cambria;Amir Hussain

  • Multimodal Sentiment Analysis: Addressing Key Issues and Setting Up the Baselines

    Soujanya Poria;Navonil Majumder;Devamanyu Hazarika;Erik Cambria

  • Empirical study of machine learning based approach for opinion mining in tweets

    Grigori Sidorov;Sabino Miranda-Jiménez;Francisco Viveros-Jiménez;Alexander Gelbukh

  • Sentiment Data Flow Analysis by Means of Dynamic Linguistic Patterns

    Soujanya Poria;Erik Cambria;Alexander Gelbukh;Federica Bisio

  • MIME: MIMicking Emotions for Empathetic Response Generation.

    Navonil Majumder;Pengfei Hong;Shanshan Peng;Jiankun Lu

Frequent Co-Authors

Soujanya Poria
Soujanya Poria Nanyang Technological University
Sivaji Bandyopadhyay
Sivaji Bandyopadhyay Jadavpur University
Erik Cambria
Erik Cambria Nanyang Technological University
Amir Hussain
Amir Hussain Edinburgh Napier University
Fabio A. González
Fabio A. González National University of Colombia
Ricardo Baeza-Yates
Ricardo Baeza-Yates Royal Institute of Technology
Rada Mihalcea
Rada Mihalcea University of Michigan–Ann Arbor
Crina Grosan
Crina Grosan King's College London
Efstathios Stamatatos
Efstathios Stamatatos University of the Aegean
Paolo Rosso
Paolo Rosso Universitat Politècnica de València

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring Computer Science often opens doors to diverse career paths in technology and business. Many students choose to supplement their studies with online degrees in related fields for maximum flexibility and value. It’s important to consider both the reputation of these programs and their costs before enrolling.

Interested in cybersecurity? Find the best cyber security online degree cost options to balance affordability with quality education. For those leaning toward project leadership roles, online programs focusing on construction management offer specialized knowledge at a lower cost. Discover a cheap online construction management degree that meets your budget and goals.

Criminal justice is another field closely aligned with computer science—especially for those interested in cybersecurity or digital forensics. Investigate the cost of criminal justice degree choices to find an affordable pathway. Finally, students with an aptitude for numbers may consider accounting. Review the best online accounting degree options for a degree that complements your computer science skills.

Best Scientists Citing Alexander Gelbukh

Trending Scientists