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Erik Cambria

Active 2009–2026

700
Papers
56,902
Citations
113
h-index
405
i10-index

Citations

Citations per year for Erik Cambria1967: 4 citations1969: 4 citations1975: 1 citations1979: 2 citations1987: 1 citations1989: 1 citations1995: 2 citations1998: 1 citations1999: 1 citations2001: 2 citations2003: 3 citations2004: 2 citations2005: 1 citations2006: 3 citations2007: 3 citations2008: 3 citations2009: 6 citations2010: 35 citations2011: 36 citations2012: 158 citations2013: 309 citations2014: 653 citations2015: 863 citations2016: 1,128 citations2017: 1,456 citations2018: 2,021 citations2019: 2,804 citations2020: 4,032 citations2021: 5,298 citations2022: 4,403 citations2023: 4,728 citations2024: 4,706 citations2025: 4,230 citations2026: 1,296 citations2027: 7 citations1968: no citations, so this year is not shown1970–1974: no citations, so these years are not shown1976–1978: no citations, so these years are not shown1980–1986: no citations, so these years are not shown1988: no citations, so this year is not shown1990–1994: no citations, so these years are not shown1996–1997: no citations, so these years are not shown2000: no citations, so this year is not shown2002: no citations, so this year is not shown

Citation sources

Countries

World map of the countries and regions citing this authorChina: 8,277 citing papers, 28.6% of this breakdownUnited States: 3,064 citing papers, 10.6% of this breakdownIndia: 1,932 citing papers, 6.7% of this breakdownUnited Kingdom: 1,434 citing papers, 5% of this breakdownSingapore: 1,007 citing papers, 3.5% of this breakdownAustralia: 827 citing papers, 2.9% of this breakdownItaly: 750 citing papers, 2.6% of this breakdownGermany: 743 citing papers, 2.6% of this breakdownSpain: 665 citing papers, 2.3% of this breakdownSouth Korea: 644 citing papers, 2.2% of this breakdownCanada: 624 citing papers, 2.2% of this breakdownJapan: 504 citing papers, 1.7% of this breakdown
0%28.6%Other 29.1%

Institutions

Fields

  • Computer Science67.1%
  • Psychology10.9%
  • Social Sciences5.4%
  • Engineering3.9%
  • Decision Sciences3%
  • Medicine1.8%
  • Other7.9%

Topics

  • Sentiment Analysis and Opinion Mining11.4%
  • Topic Modeling9.7%
  • Advanced Text Analysis Techniques6%
  • Emotion and Mood Recognition3.9%
  • Text and Document Classification Technologies3.3%
  • Natural Language Processing Techniques3%
  • Other62.7%

Coauthors

All papers

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  1. A Survey on Knowledge Graphs: Representation, Acquisition, and Applications

    Authors: Shaoxiong Ji, Shirui Pan, Erik Cambria, Pekka Marttinen, Philip S. Yu - IEEE Transactions on Neural Networks and Learning Systems, IEEE Trans. Neural Networks Learn. Syst. 2021 cited by 2,695

  2. Multimodal Language Analysis in the Wild: CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph

    Authors: Amir Zadeh, Paul Pu Liang, Soujanya Poria, Erik Cambria, Louis-Philippe Morency - Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL (1) 2018 cited by 1,211

  3. Multimodal sentiment analysis: A systematic review of history, datasets, multimodal fusion methods, applications, challenges and future directions

    Authors: Ankita Gandhi, Kinjal Adhvaryu, Soujanya Poria, Erik Cambria, Amir Hussain - Information Fusion, Inf. Fusion 2022 cited by 711

  4. Recent Trends in Deep Learning Based Natural Language Processing [Review Article]

    Authors: Tom Young, Devamanyu Hazarika, Soujanya Poria, Erik Cambria - IEEE Computational Intelligence Magazine, IEEE Comput. Intell. Mag. 2018 cited by 2,860

  5. A review of affective computing: From unimodal analysis to multimodal fusion

    Authors: Soujanya Poria, Erik Cambria, Rajiv Bajpai, Amir Hussain - Information Fusion, Inf. Fusion 2017 cited by 1,552

  6. Memory Fusion Network for Multi-view Sequential Learning

    Authors: Amir Zadeh, Paul Pu Liang, Navonil Mazumder, Soujanya Poria, Erik Cambria, Louis-Philippe Morency - AAAI Conference on Artificial Intelligence 2018 cited by 799

  7. Aspect-based sentiment analysis via affective knowledge enhanced graph convolutional networks

    Authors: Bin Liang, Hang Su, Lin Gui, Erik Cambria, Ruifeng Xu - Knowledge-Based Systems, Knowl. Based Syst. 2021 cited by 519

  8. MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

    Authors: Soujanya Poria, Devamanyu Hazarika, Navonil Majumder, Gautam Naik, Erik Cambria, Rada Mihalcea - Meeting of the Association for Computational Linguistics, ACL (1) 2019 cited by 331

  9. Context-Dependent Sentiment Analysis in User-Generated Videos

    Authors: Soujanya Poria, Erik Cambria, Devamanyu Hazarika, Navonil Majumder, Amir Zadeh, Louis-Philippe Morency - Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL (1) 2017 cited by 875

  10. ABCDM: An Attention-based Bidirectional CNN-RNN Deep Model for sentiment analysis

    Authors: Mohammad Ehsan Basiri, Shahla Nemati, Moloud Abdar, Erik Cambria, U. Rajendra Acharya - Future Generation Computer Systems, Future Gener. Comput. Syst. 2020 cited by 730

  11. Jumping NLP Curves: A Review of Natural Language Processing Research [Review Article]

    Authors: Erik Cambria, Bebo White - IEEE Computational Intelligence Magazine, IEEE Comput. Intell. Mag. 2014 cited by 1,058

  12. ICON: Interactive Conversational Memory Network for Multimodal Emotion Detection

    Authors: Devamanyu Hazarika, Soujanya Poria, Rada Mihalcea, Erik Cambria, Roger Zimmermann - Conference on Empirical Methods in Natural Language Processing, EMNLP 2018 cited by 436

  13. The Biases of Pre-Trained Language Models: An Empirical Study on Prompt-Based Sentiment Analysis and Emotion Detection

    Authors: Rui Mao, Qian Liu, Kai He, Wei Li, Erik Cambria - IEEE Transactions on Affective Computing, IEEE Trans. Affect. Comput. 2022 cited by 235

  14. Tensor Fusion Network for Multimodal Sentiment Analysis

    Authors: Amir Zadeh, Minghai Chen, Soujanya Poria, Erik Cambria, Louis-Philippe Morency - Conference on Empirical Methods in Natural Language Processing, EMNLP 2017 cited by 288

  15. A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethics

    Authors: Kai He, Rui Mao, Qika Lin, Yucheng Ruan, Xiang Lan, Mengling Feng, Erik Cambria - Information Fusion, Inf. Fusion 2025 cited by 116

  16. Conversational Memory Network for Emotion Recognition in Dyadic Dialogue Videos

    Authors: Devamanyu Hazarika, Soujanya Poria, Amir Zadeh, Erik Cambria, Louis-Philippe Morency, Roger Zimmermann - Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), NAACL-HLT 2018 cited by 454

  17. Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Survey

    Authors: Jinjie Ni, Tom Young, Vlad Pandelea, Fuzhao Xue, Vinay Adiga, Erik Cambria - Artificial Intelligence Review, Artif. Intell. Rev. 2022 cited by 223

  18. Will Affective Computing Emerge From Foundation Models and General Artificial Intelligence? A First Evaluation of ChatGPT

    Authors: Mostafa M. Amin, Erik Cambria, Björn W. Schuller - IEEE Intelligent Systems, IEEE Intell. Syst. 2023 cited by 153

  19. A survey on XAI and natural language explanations

    Authors: Erik Cambria, Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Navid Nobani - Information Processing & Management, Inf. Process. Manag. 2022 cited by 120

  20. MentalBERT: Publicly Available Pretrained Language Models for Mental Healthcare

    Authors: Shaoxiong Ji, Tianlin Zhang, Luna Ansari, Jie Fu, Prayag Tiwari, Erik Cambria - Language Resources and Evaluation Conference, LREC 2022 cited by 146

  21. Financial Sentiment Analysis: Techniques and Applications

    Authors: Kelvin Du, Frank Xing, Rui Mao, Erik Cambria - ACM Computing Surveys, ACM Comput. Surv. 2024 cited by 142

  22. KnowleNet: Knowledge fusion network for multimodal sarcasm detection

    Authors: Tan Yue, Rui Mao, Heng Wang, Zonghai Hu, Erik Cambria - Information Fusion, Inf. Fusion 2023 cited by 122

  23. Seven Pillars for the Future of Artificial Intelligence

    Authors: Erik Cambria, Rui Mao, Melvin Chen, Zhaoxia Wang, Seng-Beng Ho - IEEE Intelligent Systems, IEEE Intell. Syst. 2023 cited by 90

  24. Multi-source aggregated classification for stock price movement prediction

    Authors: Yu Ma, Rui Mao, Qika Lin, Peng Wu, Erik Cambria - Information Fusion, Inf. Fusion 2022 cited by 123