World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
50
Citations
7692
World Ranking
5710
National Ranking
218

Overview

Giuseppe Carenini is affiliated with the University of British Columbia in Canada. Their research focuses on various aspects of computer science, with particular emphasis on artificial intelligence and natural language processing techniques. Within these fields, their work extends into subfields such as computer vision and pattern recognition, sociology and political science, information systems, and epidemiology.

The main topics of their research include:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Advanced Text Analysis Techniques
  • Sentiment Analysis and Opinion Mining
  • Multimodal Machine Learning Applications
  • Speech and dialogue systems
  • Computational and Text Analysis Methods

Giuseppe Carenini has published extensively, with a notable number of papers appearing in venues such as:

  • arXiv (Cornell University)
  • Journal of Medical Internet Research
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Proceedings of the ACM on Human-Computer Interaction
  • Alzheimer s & Dementia

Some of their recent papers include:

  • Tracking COVID-19 Discourse on Twitter in North America: Infodemiology Study Using Topic Modeling and Aspect-Based Sentiment Analysis, 2021, Journal of Medical Internet Research
  • PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization, 2022, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • Tracking Public Attitudes Toward COVID-19 Vaccination on Tweets in Canada: Using Aspect-Based Sentiment Analysis, 2022, Journal of Medical Internet Research
  • Classification of Alzheimer's Disease Leveraging Multi-task Machine Learning Analysis of Speech and Eye-Movement Data, 2021, Frontiers in Human Neuroscience
  • Evaluating Web-Based Automatic Transcription for Alzheimer Speech Data: Transcript Comparison and Machine Learning Analysis, 2022, JMIR Aging

Frequent collaborators in their research include:

  • Hyeju Jang
  • Patrick Huber
  • Linzi Xing
  • Thalia S. Field
  • Gabriel Murray

Giuseppe Carenini's contributions are positioned at the intersection of computational methods and applied analysis in health and social media domains, leveraging approaches such as multi-task machine learning, sentiment analysis, and multimodal data integration.

Best Publications

  • MULTI‐DOCUMENT SUMMARIZATION OF EVALUATIVE TEXT

    Giuseppe Carenini;Jackie Chi Kit Cheung;Adam Pauls

  • Extracting knowledge from evaluative text

    Giuseppe Carenini;Raymond T. Ng;Ed Zwart

  • Multi-Document Summarization of Evaluative Text.

    Giuseppe Carenini;Raymond T. Ng;Adam Pauls

  • Abstractive Summarization of Product Reviews Using Discourse Structure

    Shima Gerani;Yashar Mehdad;Giuseppe Carenini;Raymond T. Ng

  • Combining Intra- and Multi-sentential Rhetorical Parsing for Document-level Discourse Analysis

    Shafiq Joty;Giuseppe Carenini;Raymond Ng;Yashar Mehdad

  • PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization

    Unknown

  • User-adaptive information visualization: using eye gaze data to infer visualization tasks and user cognitive abilities

    Ben Steichen;Giuseppe Carenini;Cristina Conati

  • Individual user characteristics and information visualization: connecting the dots through eye tracking

    Dereck Toker;Cristina Conati;Ben Steichen;Giuseppe Carenini

  • Codra: A novel discriminative framework for rhetorical analysis

    Shafiq Joty;Giuseppe Carenini;Raymond T. Ng

  • Generating and evaluating evaluative arguments

    Giuseppe Carenini;Johanna D. Moore

  • An intelligent interactive system for delivering individualized information to patients

    Bruce G. Buchanan;Johanna D. Moore;Diana E. Forsythe;Giuseppe Carenini

  • Describing complex charts in natural language: a caption generation system

    Vibhu O. Mittal;Giuseppe Carenini;Johanna D. Moore;Steven Roth

  • Extractive summarization of long documents by combining global and local context

    Wen Xiao;Giuseppe Carenini

  • Summarizing email conversations with clue words

    Giuseppe Carenini;Raymond T. Ng;Xiaodong Zhou

  • Tracking COVID-19 Discourse on Twitter in North America: Infodemiology Study Using Topic Modeling and Aspect-Based Sentiment Analysis.

    Hyeju Jang;Emily Rempel;David Roth;Giuseppe Carenini

  • Towards more conversational and collaborative recommender systems

    Giuseppe Carenini;Jocelyin Smith;David Poole

  • Towards adaptive information visualization: on the influence of user characteristics

    Dereck Toker;Cristina Conati;Giuseppe Carenini;Mona Haraty

  • Summarizing Spoken and Written Conversations

    Gabriel Murray;Giuseppe Carenini

  • Extractive vs. NLG-based abstractive summarization of evaluative text: the effect of corpus controversiality

    Giuseppe Carenini;Jackie Chi Kit Cheung

  • Adaptive content presentation for the web

    Andrea Bunt;Giuseppe Carenini;Cristina Conati

  • A Template-based Abstractive Meeting Summarization: Leveraging Summary and Source Text Relationships

    Tatsuro Oya;Yashar Mehdad;Giuseppe Carenini;Raymond Ng

Frequent Co-Authors

Raymond T. Ng
Raymond T. Ng University of British Columbia
Johanna D. Moore
Johanna D. Moore University of Edinburgh
Cristina Conati
Cristina Conati University of British Columbia
Shafiq Joty
Shafiq Joty Salesforce (United States)
Steven F. Roth
Steven F. Roth Carnegie Mellon University
David Poole
David Poole University of British Columbia
Huamin Qu
Huamin Qu Hong Kong University of Science and Technology
Per Ola Kristensson
Per Ola Kristensson University of Cambridge
Shixia Liu
Shixia Liu Tsinghua University
Alan K. Mackworth
Alan K. Mackworth University of British Columbia

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