Sentiment Analysis and Opinion Mining
Encyclopedia of Machine Learning and Data MiningPublished 1 January 2017
Lei Zhang, Bing Liu
Citations3,319
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
Abstract
With the rapid growth of social media, sentiment analysis, also called opinion mining, has become one of the most active research areas in natural language processing. Its application is also widespread, from business services to political campaigns. This article gives an introduction to this important area and presents some recent developments.
Keywords
Computer Science
Journal of Machine Learning ResearchLatent dirichlet allocation
27,049 Citations2003David M. Blei, Andrew Y. Ng +1 more
Proceedings of the IEEEA tutorial on hidden Markov models and selected applications in speech recognition
22,785 Citations1989L. R. Rabiner
Journal of Electronic ImagingPattern Recognition and Machine Learning
21,976 Citations2007Christopher Bishop
Probability Distributions, linear models for Regression, Linear Models for Classification, Neural Networks, Graphical Models, Mixture Models and EM, Sampling Methods, Continuous Latent Variables, Sequential Data are studied.
The PageRank Citation Ranking : Bringing Order to the Web
12,645 Citations1999Lawrence M. Page, Sergey Brin +2 more
This paper describes PageRank, a mathod for rating Web pages objectively and mechanically, effectively measuring the human interest and attention devoted to them, and shows how to efficiently compute PageRank for large numbers of pages.
Journal of the ACMAuthoritative sources in a hyperlinked environment
9,060 Citations1999Jon Kleinberg
This work proposes and test an algorithmic formulation of the notion of authority, based on the relationship between a set of relevant authoritative pages and the set of “hub pages” that join them together in the link structure, and has connections to the eigenvectors of certain matrices associated with the link graph.
Mining and summarizing customer reviews
7,714 Citations2004Minqing Hu, Bing Liu
This research aims to mine and to summarize all the customer reviews of a product, and proposes several novel techniques to perform these tasks.
Thumbs up?
6,987 Citations2002Bo Pang, Lillian Lee +1 more
This work considers the problem of classifying documents not by topic, but by overall sentiment, e.g., determining whether a review is positive or negative, and concludes by examining factors that make the sentiment classification problem more challenging.
Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank
6,774 Citations2013Richard Socher, Alex Perelygin +5 more
A Sentiment Treebank that includes fine grained sentiment labels for 215,154 phrases in the parse trees of 11,855 sentences and presents new challenges for sentiment compositionality, and introduces the Recursive Neural Tensor Network.
Technical reportsMaking Large-Scale SVM Learning Practical
4,317 Citations2006Thorsten Joachims
This chapter presents algorithmic and computational results developed for SVM light V 2.0, which make large-scale SVM training more practical and give guidelines for the application of SVMs to large domains.
International Journal of LexicographyIntroduction to WordNet: An On-line Lexical Database<sup>*</sup>
4,207 Citations1990George A. Miller, Richard Beckwith +3 more
Standard alphabetical procedures for organizing lexical information put together words that are spelled alike and scatter words with similar or related meanings haphazardly through the list.
Meeting of the Association for Computational LinguisticsThumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews
3,654 Citations2002Peter Peter, Turney
Recognizing contextual polarity in phrase-level sentiment analysis
3,379 Citations2005Theresa Wilson, Janyce Wiebe +1 more
A new approach to phrase-level sentiment analysis is presented that first determines whether an expression is neutral or polar and then disambiguates the polarity of the polar expressions.
A sentimental education
3,343 Citations2004Bo Pang, Lillian Lee
A novel machine-learning method is proposed that applies text-categorization techniques to just the subjective portions of the document, which greatly facilitates incorporation of cross-sentence contextual constraints.
Learning Word Vectors for Sentiment Analysis
3,299 Citations2011Andrew L. Maas, Raymond E. Daly +4 more
This work presents a model that uses a mix of unsupervised and supervised techniques to learn word vectors capturing semantic term--document information as well as rich sentiment content, and finds it out-performs several previously introduced methods for sentiment classification.
Integrating classification and association rule mining
2,223 Citations1998Bing Liu, Wynne Hsu +1 more
The integration is done by focusing on mining a special subset of association rules, called class association rules (CARs), and shows that the classifier built this way is more accurate than that produced by the state-of-the-art classification system C4.5.
Machine LearningBoosTexter: A Boosting-based System for Text Categorization
2,194 Citations2000Robert E. Schapire, Yoram Singer
This work describes in detail an implementation, called BoosTexter, of the new boosting algorithms for text categorization tasks, and presents results comparing the performance of Boos Texter and a number of other text-categorization algorithms on a variety of tasks.
Seeing stars
2,127 Citations2005Bo Pang, Lillian Lee
A meta-algorithm is applied, based on a metric labeling formulation of the rating-inference problem, that alters a given n-ary classifier's output in an explicit attempt to ensure that similar items receive similar labels.
arXiv (Cornell University)Probabilistic Latent Semantic Analysis
2,092 Citations2013Thomas Hofmann
This work proposes a widely applicable generalization of maximum likelihood model fitting by tempered EM, based on a mixture decomposition derived from a latent class model which results in a more principled approach which has a solid foundation in statistics.
International Journal of Electronic CommerceThe Effect of On-Line Consumer Reviews on Consumer Purchasing Intention: The Moderating Role of Involvement
2,065 Citations2007Do-Hyung Park, Jumin Lee +1 more
The elaboration likelihood model is used to explain how level of involvement with a product moderates these relationships, and the quality of on-line reviews has a positive effect on consumers' purchasing intention and purchasing intention increases as the number of reviews increases.
Predicting the Future with Social Media
2,064 Citations2010Sitaram Asur, Bernardo A. Huberman
Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classification
2,026 Citations2007John Blitzer, Mark Dredze +1 more
This work extends to sentiment classification the recently-proposed structural correspondence learning (SCL) algorithm, reducing the relative error due to adaptation between domains by an average of 30% over the original SCL algorithm and 46% over a supervised baseline.
Proceedings of the International AAAI Conference on Web and Social MediaFrom Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series
1,955 Citations2010Brendan O’Connor, Ramnath Balasubramanyan +2 more
This work connects measures of public opinion measured from polls with sentiment measured from text, and finds that temporal smoothing is a critically important issue to support a suc- cessful model.
Mining the peanut gallery
1,908 Citations2003Kushal Dave, Steve Lawrence +1 more
This work develops a method for automatically distinguishing between positive and negative reviews and draws on information retrieval techniques for feature extraction and scoring, and the results for various metrics and heuristics vary depending on the testing situation.
Synthesis lectures on human language technologiesSentiment Analysis and Opinion Mining
1,761 Citations2012Bing Liu
Texas ScholarWorks (Texas Digital Library)The Development and Psychometric Properties of LIWC2015
1,678 Citations2015James W. Pennebaker, Cindy K. Chung +2 more
Opinion observer
1,604 Citations2005Bing Liu, Minqing Hu +1 more
A novel framework for analyzing and comparing consumer opinions of competing products is proposed, and a new technique based on language pattern mining is proposed to extract product features from Pros and Cons in a particular type of reviews.
Sentiment Analysis and Subjectivity
1,594 Citations2010Liu Bing
An intraocular lens for implantation in an eye comprising an optic configured so that the optic can be deformed to permit the intraocular Lens to be passed through an incision into the eye is provided.
Learning from Labeled and Unlabeled Data with Label Propagation
1,568 Citations2002Xiongjie Zhu, Zoubin Ghahramani
A simple iterative algorithm, label propagation, to propagate labels through the dataset along high density areas defined by unlabeled data is proposed and its solution is analyzed, and its connection to several other algorithms is analyzed.
Domain adaptation with structural correspondence learning
1,562 Citations2006John Blitzer, Ryan McDonald +1 more
This work introduces structural correspondence learning to automatically induce correspondences among features from different domains in order to adapt existing models from a resource-rich source domain to aresource-poor target domain.
Automatic retrieval and clustering of similar words
1,555 Citations1998Dekang Lin
A word similarity measure based on the distributional pattern of words allows the automatically constructed thesaurus to be significantly closer to WordNet than Roget Thesaurus is.
Journal of Interactive MarketingExploring the value of online product reviews in forecasting sales: The case of motion pictures
1,531 Citations2007Chrysanthos Dellarocas, Xiaoquan Zhang +1 more
This study shows that the addition of online product review metrics to a benchmark model that includes prerelease marketing, theater availability and professional critic reviews substantially increases its forecasting accuracy; the forecasting accuracy of the best model outperforms that of several previously published models.
ACM Transactions on Information SystemsMeasuring praise and criticism
1,509 Citations2003Peter D. Turney, Michael L. Littman
This article introduces a method for inferring the semantic orientation of a word from its statistical association with a set of positive and negative paradigm words, based on two different statistical measures of word association.
Personality and Social Psychology BulletinLying Words: Predicting Deception from Linguistic Styles
1,457 Citations2003Matthew L. Newman, James W. Pennebaker +2 more
Management ScienceYahoo! for Amazon: Sentiment Extraction from Small Talk on the Web
1,442 Citations2007Sanjiv Ranjan Das, Mike Y. Chen
A methodology for extracting small investor sentiment from stock message boards is developed, which comprises different classifier algorithms coupled together by a voting scheme.
Predicting the semantic orientation of adjectives
1,439 Citations1997Vasileios Hatzivassiloglou, Kathleen McKeown
A log-linear regression model uses constraints from conjunctions to predict whether conjoined adjectives are of same or different orientations, achieving 82% accuracy in this task when each conjunction is considered independently.
Detecting Lies and Deceit: Pitfalls and Opportunities
1,310 Citations2008Aldert Vrij
Choice Reviews OnlineWeb data mining: exploring hyperlinks, contents, and usage data
1,193 Citations2012
Sentiment analysis
1,158 Citations2003Tetsuya Nasukawa, Jeonghee Yi
This paper illustrates a sentiment analysis approach to extract sentiments associated with polarities of positive or negative for specific subjects from a document, instead of classifying the whole document intopositive or negative.
Computational LinguisticsOpinion Word Expansion and Target Extraction through Double Propagation
1,100 Citations2011Guang Qiu, Bing Liu +2 more
This article study two important problems, namely, opinion lexicon expansion and opinion target extraction, and proposes a method based on bootstrapping that outperforms these existing methods significantly.
Handbook of Natural Language Processing
1,080 Citations2010Nitin Indurkhya, Fred J. Damerau
Fully updated with the latest developments in the field, this comprehensive, modern handbook emphasizes how to implement practical language processing tools in computational systems.
Éléments de syntaxe structurale
1,067 Citations1959Lucien Tesnière
Towards answering opinion questions
1,051 Citations2003Hong Yu, Vasileios Hatzivassiloglou
A Bayesian classifier for discriminating between documents with a preponderance of opinions such as editorials from regular news stories is presented, and three unsupervised, statistical techniques for the significantly harder task of detecting opinions at the sentence level are described.
Learning extraction patterns for subjective expressions
1,001 Citations2003Ellen Riloff, Janyce Wiebe
A bootstrapping process that learns linguistically rich extraction patterns for subjective (opinionated) expressions while maintaining high precision is presented.
Research Showcase @ Carnegie Mellon University (Carnegie Mellon University)Learning from Labeled and Unlabeled Data using Graph Mincuts
947 Citations2018Avrim Blum, Shuchi Chawla
An algorithm based on finding minimum cuts in graphs, that uses pairwise relationships among the examples in order to learn from both labeled and unlabeled data is considered.
Movie review mining and summarization
909 Citations2006Zhuang Li, Jing Feng +1 more
A multi-knowledge based approach is proposed, which integrates WordNet, statistical analysis and movie knowledge, and the experimental results show the effectiveness of the proposed approach in movie review mining and summarization.
ACM Transactions on Information SystemsSentiment analysis in multiple languages
894 Citations2008Ahmed Abbasi, Hsinchun Chen +1 more
Stylistic features significantly enhanced performance across all testbeds while EWGA also outperformed other feature selection methods, indicating the utility of these features and techniques for document-level classification of sentiments.
Robust Sentiment Detection on Twitter from Biased and Noisy Data
875 Citations2010Luciano Barbosa, Junlan Feng
This paper proposes an approach to automatically detect sentiments on Twitter messages (tweets) that explores some characteristics of how tweets are written and meta-information of the words that compose these messages and leverages sources of noisy labels as training data.
NPARCEmotions Evoked by Common Words and Phrases: Using Mechanical Turk to Create an Emotion Lexicon
873 Citations2010Saif M. Mohammad, Peter D. Turney
This paper shows how to create a high-quality, moderate-sized emotion lexicon using Mechanical Turk, and identifies which emotions tend to be evoked simultaneously by the same term and shows that certain emotions indeed go hand in hand.
Target-dependent Twitter Sentiment Classification
846 Citations2011Long Jiang, Mo Yu +3 more
This paper proposes to improve target-dependent Twitter sentiment classification by incorporating target- dependent features; and taking related tweets into consideration; and according to the experimental results, this approach greatly improves the performance of target- dependence sentiment classification.
Predicting the semantic orientation of adjectives
819 Citations1997Vasileios Hatzivassiloglou, Kathleen McKeown
International Journal on Digital LibrariesAutomatic recognition of multi-word terms:. the C-value/NC-value method
818 Citations2000Katerina T. Frantzi, Sophia Ananiadou +1 more
This paper presents a domain-independent method for the automatic extraction of multi-word terms, from machine-readable special language corpora, using C-value/NC-value, which enhances the common statistical measure of frequency of occurrence for term extraction, making it sensitive to a particular type ofMulti- word terms, the nested terms.
Topic sentiment mixture
813 Citations2007Qiaozhu Mei, Xu Ling +3 more
The proposed Topic-Sentiment Mixture (TSM) model can reveal the latent topical facets in a Weblog collection, the subtopics in the results of an ad hoc query, and their associated sentiments and could also provide general sentiment models that are applicable to any ad hoc topics.
Modeling online reviews with multi-grain topic models
792 Citations2008Ivan Titov, Ryan McDonald
This paper presents a novel framework for extracting ratable aspects of objects from online user reviews and argues that multi-grain models are more appropriate for this task since standard models tend to produce topics that correspond to global properties of objects rather than aspects of an object that tend to be rated by a user.
Cross-domain sentiment classification via spectral feature alignment
789 Citations2010Sinno Jialin Pan, Xiaochuan Ni +3 more
This work develops a general solution to sentiment classification when the authors do not have any labels in a target domain but have some labeled data in a different domain, regarded as source domain and proposes a spectral feature alignment (SFA) algorithm to align domain-specific words from different domains into unified clusters, with the help of domain-independent words as a bridge.
Emotions from text
785 Citations2005Cecilia Ovesdotter Alm, Dan Roth +1 more
This paper explores the text-based emotion prediction problem empirically, using supervised machine learning with the SNoW learning architecture to classify the emotional affinity of sentences in the narrative domain of children's fairy tales, for subsequent usage in appropriate expressive rendering of text-to-speech synthesis.
Aspect and sentiment unification model for online review analysis
772 Citations2011Yohan Jo, Alice Oh
This paper proposes Sentence-LDA and extends it to Aspect and Sentiment Unification Model (ASUM), which incorporates aspect and sentiment together to model sentiments toward different aspects and shows that ASUM outperforms other generative models and comes close to supervised classification methods.
Spotting fake reviewer groups in consumer reviews
747 Citations2012Arjun Mukherjee, Bing Liu +1 more
This paper studies spam detection in the collaborative setting, i.e., to discover fake reviewer groups by using several behavioral models derived from the collusion phenomenon among fake reviewers and relation models based on the relationships among groups, individual reviewers, and products they reviewed to detectfake reviewer groups.
Computational LinguisticsLearning Subjective Language
743 Citations2004Janyce Wiebe, Theresa Wilson +3 more
This article shows that the density of subjectivity clues in the surrounding context strongly affects how likely it is that a word is subjective, and it provides the results of an annotation study assessing the subjectivity of sentences with high-density features.
Detecting product review spammers using rating behaviors
720 Citations2010Ee‐Peng Lim, Viet-An Nguyen +3 more
This paper identifies several characteristic behaviors of review spammers and model these behaviors so as to detect the spammers, and shows that the detected spammers have more significant impact on ratings compared with the unhelpful reviewers.
Sentiment analyzer: extracting sentiments about a given topic using natural language processing techniques
720 Citations2004Junbo Yi, Tetsuya Nasukawa +2 more
This work presents sentiment analyzer (SA) that extracts sentiment (or opinion) about a subject from online text documents using natural language processing (NLP) techniques.
Improving machine learning approaches to coreference resolution
709 Citations2001Vincent Ng, Claire Cardie
A noun phrase coreference system that extends the work of Soon et al. (2001) and produces the best results to date on the M UC-6 and MUC-7 coreference resolution data sets --- F-measures of 70.4 and 63.4, respectively.
Enhanced Sentiment Learning Using Twitter Hashtags and Smileys
705 Citations2010Dmitry Davidov, Oren Tsur +1 more
A supervised sentiment classification framework which is based on data from Twitter, a popular microblogging service, is proposed, utilizing 50 Twitter tags and 15 smileys as sentiment labels, allowing identification and classification of diverse sentiment types of short texts.
Wiley Interdisciplinary Reviews Computational StatisticsSupport vector machines
692 Citations2009Alessia Mammone, Marco Turchi +1 more
arXiv (Cornell University)Finding Deceptive Opinion Spam by Any Stretch of the Imagination
688 Citations2011Myle Ott, Yejin Choi +2 more
Effects of adjective orientation and gradability on sentence subjectivity
671 Citations2000Vasileios Hatzivassiloglou, Janyce Wiebe
A novel trainable method that statistically combines two indicators of gradability is presented and evaluated, complementing existing automatic techniques for assigning orientation labels.
Studies in linguistics and philosophyIntroduction to Montague Semantics
652 Citations1980David R. Dowty, Robert E. Wall +1 more
This book discusses Montague's Intensional Logic, a Higher-Order Type-Theoretic Language, and some Unresolved Issues with Possible Worlds Semantics and Propositional Attitudes.
A Joint Model of Text and Aspect Ratings for Sentiment Summarization
638 Citations2008Ivan Titov, Ryan McDonald
A statistical model is proposed which is able to discover corresponding topics in text and extract textual evidence from reviews supporting each of these aspect ratings, a fundamental problem in aspect-based sentiment summarization.
Identifying Sarcasm in Twitter: A Closer Look
632 Citations2011Roberto González‐Ibáñez, Smaranda Muresan +1 more
This work reports on a method for constructing a corpus of sarcastic Twitter messages in which determination of the sarcasm of each message has been made by its author and uses this reliable corpus to compare sarcastic utterances in Twitter to utterances that express positive or negative attitudes without sarcasm.
Sarcasm as Contrast between a Positive Sentiment and Negative Situation
591 Citations2013Ellen Riloff, Ashequl Qadir +4 more
This work develops a sarcasm recognizer that automatically learns lists of positive sentiment phrases and negative situation phrases from sarcastic tweets and shows that identifying contrasting contexts using the phrases learned through bootstrapping yields improved recall for sarcasm recognition.
Measures of distributional similarity
586 Citations1999Lillian Lee
This work presents an empirical comparison of a broad range of measures; a classification of similarity functions based on the information that they incorporate; and the introduction of a novel function that is superior at evaluating potential proxy distributions.
Journal of Experimental Psychology GeneralHow to be sarcastic: The echoic reminder theory of verbal irony.
546 Citations1989Roger J. Kreuz, Sam Glucksberg
Lecture notes in computer scienceCreating Subjective and Objective Sentence Classifiers from Unannotated Texts
543 Citations2005Janyce Wiebe, Ellen Riloff
The results of developing subjectivity classifiers using only unannotated texts for training rivals that of previous supervised learning approaches and advances the state of the art in objective sentence classification.
Emotions in social psychology : essential readings
543 Citations2001W. Gerrod Parrott
Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign)Opinosis: A Graph Based Approach to Abstractive Summarization of Highly Redundant Opinions
524 Citations2010Kavita Ganesan, ChengXiang Zhai +1 more
A novel graph-based summarization framework (Opinosis) that generates concise abstractive summaries of highly redundant opinions that have better agreement with human summaries compared to the baseline extractive method.
Learning Subjective Adjectives from Corpora
520 Citations2000Janyce Wiebe
This paper identifies strong clues of subjectivity using the results of a method for clustering words according to distributional similarity (Lin 1998), seeded by a small amount of detailed manual annotation.
Partially Supervised Classification of Text Documents
516 Citations2002Bing Liu, Wee Sun Lee +2 more
This paper shows that the problem of identifying documents from a set of documents of a particular topic or class P and a large set M of mixed documents, and that under appropriate conditions, solutions to the constrained optimization problem will give good solution to the partially supervised classification problem.
Discourse ProcessesOn Lying and Being Lied To: A Linguistic Analysis of Deception in Computer-Mediated Communication
514 Citations2007Jeffrey T. Hancock, Lauren E. Curry +2 more
Investigating changes in both the liar's and the conversational partner's linguistic style across truthful and deceptive dyadic communication in a synchronous text-based setting revealed that motivated liars avoided causal terms when lying, whereas unmotivated liars tended to increase their use of negations.
An Unsupervised Aspect-Sentiment Model for Online Reviews
507 Citations2010Samuel Brody, Noémie Elhadad
An unsuper-vised system for extracting aspects and determining sentiment in review text is presented, which is simple and flexible with regard to domain and language, and takes into account the influence of aspect on sentiment polarity.
Co-training for cross-lingual sentiment classification
499 Citations2009Xiaojun Wan
A cotraining approach is proposed to making use of unlabeled Chinese data for cross-lingual sentiment classification, which leverages an available English corpus for Chinese sentiment classification by using the English corpus as training data.
Journal of PragmaticsVerbal irony as implicit display of ironic environment: Distinguishing ironic utterances from nonirony
490 Citations2000Akira Utsumi
Opinion Mining and Sentiment Analysis
480 Citations2011Bing Liu
This chapter focuses on mining opinions which indicate positive or negative sentiments, which are of great importance for businesses and consumers wanting to find public or consumer opinions on their products and services.
TUbilio (Technical University of Darmstadt)Extracting Opinion Targets in a Single and Cross-Domain Setting with Conditional Random Fields
480 Citations2010Niklas Jakob, Iryna Gurevych
This paper model the problem as an information extraction task, which is addressed based on Conditional Random Fields (CRF), and employs the supervised algorithm by Zhuang et al. (2006), which represents the state-of-the-art on the employed data.
Opinion Extraction, Summarization and Tracking in News and Blog Corpora.
477 Citations2006Lun‐Wei Ku, Yuting Liang +1 more
Both news and web blog articles are investigated and algorithms for opinion extraction at word, sentence and document level are proposed, and the issue of relevant sentence selection is discussed, and then topical and opinionated information are summarized.
Information RetrievalA machine learning approach to sentiment analysis in multilingual Web texts
473 Citations2008Erik Boiy, Marie‐Francine Moens
This paper presents machine learning experiments with regard to sentiment analysis in blog, review and forum texts found on the World Wide Web and written in English, Dutch and French and investigates the role of active learning techniques for reducing the number of examples to be manually annotated.
Extracting opinions, opinion holders, and topics expressed in online news media text
460 Citations2006Soo-Min Kim, Eduard Hovy
This method uses semantic role labeling as an intermediate step to label an opinion holder and topic using data from FrameNet, and decomposes the task into three phases: identifying an opinion-bearing word, labeling semantic roles related to the word in the sentence, and then finding the holder and the topic of the opinion word among the labeled semantic roles.
Automatically constructing a dictionary for information extraction tasks
453 Citations1993Ellen Riloff
Using AutoSlog, a system that automatically builds a domain-specific dictionary of concepts for extracting information from text, a dictionary for the domain of terrorist event descriptions was constructed in only 5 person-hours and the overall scores were virtually indistinguishable.
Identifying comparative sentences in text documents
445 Citations2006Nitin Jindal, Bing Liu
This paper first categorizes comparative sentences into different types, and then presents a novel integrated pattern discovery and supervised learning approach to identifying comparative sentences from text documents.
Lecture notes in computer sciencePulse: Mining Customer Opinions from Free Text
444 Citations2005Michael Gamon, Anthony Aue +2 more
A simple but effective technique for clustering sentences, the application of a bootstrapping approach to sentiment classification, and a novel user-interface are described that enables the exploration of large quantities of customer free text.
Just how mad are you? finding strong and weak opinion clauses
435 Citations2004Theresa Wilson, Janyce Wiebe +1 more
This paper presents the first experimental results classifying the strength of opinions and other types of subjectivity and classifies the subjectivity of deeply nested clauses using new syntactic features developed for opinion recognition.
Expanding domain sentiment lexicon through double propagation
415 Citations2009Guang Qiu, Bing Liu +2 more
A novel propagation approach is proposed that exploits the relations between sentiment words and topics or product features that the sentiment words modify, and also sentiment Words and product features themselves to extract new sentiment words.
Singapore Management University Institutional Knowledge (InK) (Singapore Management University)Jointly Modeling Aspects and Opinions with a MaxEnt-LDA Hybrid
414 Citations2010Xin Zhao, Jing Jiang +2 more
This paper proposes a MaxEnt-LDA hybrid model to jointly discover both aspects and aspect-specific opinion words and shows that with a relatively small amount of training data, this model can effectively identify aspect and opinion words simultaneously.
Extracting semantic orientations of words using spin model
407 Citations2005Hiroya Takamura, Takashi Inui +1 more
The mean field approximation is used to compute the approximate probability function of the system instead of the intractable actual probability function, and a criterion for parameter selection on the basis of magnetization is proposed.
Low-Quality Product Review Detection in Opinion Summarization
392 Citations2007Jingjing Liu, Yunbo Cao +3 more
Experimental results show that the proposed approach effectively discriminates lowquality reviews from high-quality ones and enhances the task of opinion summarization by detecting and filtering low quality reviews.
Building a Sentiment Summarizer for Local Service Reviews
391 Citations2008Sasha Blair-Goldensohn, Kerry Hannan +4 more
This paper presents a system that summarizes the sen- timent of reviews for a local service such as a restaurant or hotel using aspect-based summarization models, where a summary is built by extracting relevant aspects of a service, such as service or value, aggregating the sentiment per aspect, and selecting aspect-relevant text.
Topic sentiment analysis in twitter
390 Citations2011Xiaolong Wang, Furu Wei +3 more
This study focuses on hashtag-level sentiment classification, which aims to automatically generate the overall sentiment polarity for a given hashtag in a certain time period, and proposes a novel graph model and three approximate collective classification algorithms for inference.
Determining the semantic orientation of terms through gloss classification
388 Citations2005Andrea Esuli, Fabrizio Sebastiani
This paper presents a new method for determining the orientation of subjective terms based on the quantitative analysis of the glosses of such terms given in on-line dictionaries, and on the use of the resulting term representations for semi-supervised term classification.
…
