Who Cited It

Thumbs up? Sentiment Classification using Machine Learning Techniques

2002 · arXiv (Cornell University) · 2,215 citations · 9 from inside this corpus

Bo Pang, Lillian Lee, Shivakumar Vaithyanathan

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

Thumbs up? Sentiment Classification using Machine Learning Techniques (2002)Thumbs up? Sentiment Classifi…Text categorization with Support Vector Machines: Learning with many relevant features (1998)Text categorization with Supp…Making Large-Scale SVM Learning Practical (2006)Making Large-Scale SVM Learni…Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of … (2002)Thumbs Up or Thumbs Down? Sem…A comparison of event models for naive bayes text classification (1998)A comparison of event models …A maximum entropy approach to natural language processing (1996)A maximum entropy approach to…Naive (Bayes) at forty: The independence assumption in information retrieval (1998)Naive (Bayes) at forty: The i…A systematic analysis of performance measures for classification tasks (2009)A systematic analysis of perf…A theory of learning from different domains (2009)A theory of learning from dif…A sentimental education (2004)A sentimental educationFrom Frequency to Meaning: Vector Space Models of Semantics (2010)From Frequency to Meaning: Ve…Seeing stars (2005)Seeing starsSemEval-2014 Task 4: Aspect Based Sentiment Analysis (2014)SemEval-2014 Task 4: Aspect B…Extracting product features and opinions from reviews (2005)Extracting product features a…The text mining handbook: advanced approaches in analyzing unstructured data (2007)The text mining handbook: adv…Determining the sentiment of opinions (2004)Determining the sentiment of …
15 of 15 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
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What this paper cites, inside the corpus

PaperYearCited
Text categorization with Support Vector Machines: Learning with many relevant features19988,044
Making Large-Scale SVM Learning Practical20064,326
Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of …20023,661
A comparison of event models for naive bayes text classification19983,225
A maximum entropy approach to natural language processing19963,129
Naive (Bayes) at forty: The independence assumption in information retrieval19982,114

What cites it, inside the corpus

PaperYearCited
A systematic analysis of performance measures for classification tasks20096,889
A theory of learning from different domains20093,607
A sentimental education20043,353
From Frequency to Meaning: Vector Space Models of Semantics20102,902
Seeing stars20052,164
SemEval-2014 Task 4: Aspect Based Sentiment Analysis20141,915
Extracting product features and opinions from reviews20051,719
The text mining handbook: advanced approaches in analyzing unstructured data20071,626
Determining the sentiment of opinions20041,494

Links

DOI · Open access copy · OpenAlex record

Topics

Sentiment Analysis and Opinion MiningComputer Science
Text and Document Classification TechnologiesComputer Science
Topic ModelingComputer Science

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports3 author record(s) attached.
  • supports21 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:50+00:00.

sha256 86a6d6715ff540a0…