D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 38 Citations 35,539 65 World Ranking 5004 National Ranking 2463

Research.com Recognitions

Awards & Achievements

2018 - ACM Fellow For contributions to natural language processing, sentiment analysis, and computational social science

2002 - Fellow of Alfred P. Sloan Foundation

Overview

What is she best known for?

The fields of study she is best known for:

  • Artificial intelligence
  • Machine learning
  • Natural language processing

Her scientific interests lie mostly in Artificial intelligence, Natural language processing, Sentiment analysis, Support vector machine and Machine learning. Her research integrates issues of Social relation, Situational ethics and Cognitive psychology in her study of Artificial intelligence. Her studies deal with areas such as Bigram and Word as well as Natural language processing.

Her Sentiment analysis study incorporates themes from Subjectivity and Automatic summarization. Her Subjectivity study combines topics from a wide range of disciplines, such as Popularity, Information extraction and Object. In her research, Naive Bayes classifier, Principle of maximum entropy, Class, Similarity and Semantic similarity is intimately related to Categorization, which falls under the overarching field of Support vector machine.

Her most cited work include:

  • Opinion Mining and Sentiment Analysis (5838 citations)
  • Thumbs up? Sentiment Classification using Machine Learning Techniques (5728 citations)
  • A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts (2717 citations)

What are the main themes of her work throughout her whole career to date?

Her primary scientific interests are in Artificial intelligence, Natural language processing, Parsing, Information retrieval and Language model. Her research on Artificial intelligence frequently links to adjacent areas such as Machine learning. Her Natural language processing research incorporates elements of Bigram, Word, Speech recognition and Similarity.

Her Information retrieval research is multidisciplinary, incorporating perspectives in Hyperlink and Centrality. Her research in Sentiment analysis intersects with topics in Subjectivity, Support vector machine and Automatic summarization. Her study focuses on the intersection of Support vector machine and fields such as Categorization with connections in the field of Naive Bayes classifier and Principle of maximum entropy.

She most often published in these fields:

  • Artificial intelligence (45.93%)
  • Natural language processing (34.81%)
  • Parsing (13.33%)

What were the highlights of her more recent work (between 2017-2021)?

  • Artificial intelligence (45.93%)
  • Natural language processing (34.81%)
  • Parsing (13.33%)

In recent papers she was focusing on the following fields of study:

Her main research concerns Artificial intelligence, Natural language processing, Parsing, Dependency and Annotation. Lillian Lee performs multidisciplinary study in Artificial intelligence and Structure in her work. The various areas that Lillian Lee examines in her Natural language processing study include Concreteness, Image and Table.

Lillian Lee has researched Parsing in several fields, including F1 score, Web page and Machine translation. Her Dependency study combines topics in areas such as Theoretical computer science and Projective test. The concepts of her Annotation study are interwoven with issues in Sentence, Test and Multi-image.

Between 2017 and 2021, her most popular works were:

  • Quantifying the Visual Concreteness of Words and Topics in Multimodal Datasets (16 citations)
  • Unsupervised Discovery of Multimodal Links in Multi-image, Multi-sentence Documents (11 citations)
  • Something's Brewing! Early Prediction of Controversy-causing Posts from Discussion Features. (11 citations)

In her most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Natural language processing

Her primary areas of study are Natural language processing, Artificial intelligence, Cognitive psychology, Dependency grammar and Concreteness. Her Natural language processing research is mostly focused on the topic Sentence. Her Cognitive psychology study frequently links to related topics such as Conversation.

Her Dependency grammar research includes elements of Valency, Tree-adjoining grammar, Treebank, Projective test and Syntax. Her Concreteness study frequently links to adjacent areas such as Image.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Thumbs up? Sentiment Classification using Machine Learning Techniques

Bo Pang;Lillian Lee;Shivakumar Vaithyanathan.
empirical methods in natural language processing (2002)

9706 Citations

Opinion Mining and Sentiment Analysis

Bo Pang;Lillian Lee.
(2008)

8811 Citations

A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts

Bo Pang;Lillian Lee.
meeting of the association for computational linguistics (2004)

4087 Citations

Seeing Stars: Exploiting Class Relationships for Sentiment Categorization with Respect to Rating Scales

Bo Pang;Lillian Lee.
meeting of the association for computational linguistics (2005)

2036 Citations

DISTRIBUTIONAL CLUSTERING OF ENGLISH WORDS

Fernando Pereira;Naftali Tishby;Lillian Lee.
meeting of the association for computational linguistics (1993)

1423 Citations

Measures of Distributional Similarity

Lillian Lee.
meeting of the association for computational linguistics (1999)

795 Citations

Get out the vote: Determining support or opposition from Congressional floor-debate transcripts

Matt Thomas;Bo Pang;Lillian Lee.
empirical methods in natural language processing (2006)

616 Citations

Learning to paraphrase: an unsupervised approach using multiple-sequence alignment

Regina Barzilay;Lillian Lee.
north american chapter of the association for computational linguistics (2003)

584 Citations

Similarity-Based Models of Word Cooccurrence Probabilities

Ido Dagan;Lillian Lee;Fernando C. N. Pereira.
Machine Learning (1999)

565 Citations

User-level sentiment analysis incorporating social networks

Chenhao Tan;Lillian Lee;Jie Tang;Long Jiang.
knowledge discovery and data mining (2011)

440 Citations

Best Scientists Citing Lillian Lee

Bing Liu

Bing Liu

Peking University

Publications: 87

Erik Cambria

Erik Cambria

Nanyang Technological University

Publications: 77

Pushpak Bhattacharyya

Pushpak Bhattacharyya

Indian Institute of Technology Patna

Publications: 64

Ting Liu

Ting Liu

Harbin Institute of Technology

Publications: 51

Claire Cardie

Claire Cardie

Cornell University

Publications: 48

Guodong Zhou

Guodong Zhou

Soochow University

Publications: 47

Saif M. Mohammad

Saif M. Mohammad

National Research Council Canada

Publications: 47

Noah A. Smith

Noah A. Smith

University of Washington

Publications: 45

Soujanya Poria

Soujanya Poria

Singapore University of Technology and Design

Publications: 44

Janyce Wiebe

Janyce Wiebe

University of Pittsburgh

Publications: 40

Eduard Hovy

Eduard Hovy

Carnegie Mellon University

Publications: 37

ChengXiang Zhai

ChengXiang Zhai

University of Illinois at Urbana-Champaign

Publications: 36

Rada Mihalcea

Rada Mihalcea

University of Michigan–Ann Arbor

Publications: 35

Mirella Lapata

Mirella Lapata

University of Edinburgh

Publications: 35

Ido Dagan

Ido Dagan

Bar-Ilan University

Publications: 34

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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