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473,973
A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts
- In Proceedings of the ACL
, 2004
"... Sentiment analysis seeks to identify the viewpoint(s) underlying a text span; an example application is classifying a movie review as “thumbs up” or “thumbs down”. To determine this sentiment polarity, we propose a novel machine-learning method that applies text-categorization techniques to just the ..."
Abstract
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Cited by 589 (7 self)
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the subjective portions of the document. Extracting these portions can be implemented using efficient techniques for finding minimum cuts in graphs; this greatly facilitates incorporation of cross-sentence contextual constraints. Publication info: Proceedings of the ACL, 2004. 1
A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts
"... Sentiment analysis seeks to identify the viewpoint(s) underlying a text span; an example application is classifying a movie review as “thumbs up” or “thumbs down”. To determine this sentiment polarity, we propose a novel machine-learning method that applies text-categorization techniques to just the ..."
Abstract
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the subjective portions of the document. Extracting these portions can be implemented using efficient techniques for finding minimum cuts in graphs; this greatly facilitates incorporation of cross-sentence contextual constraints. Publication info: Proceedings of the ACL, 2004. 1
A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts
"... Sentiment analysis seeks to identify the viewpoint(s) underlying a text span; an example application is classifying a movie review as “thumbs up” or “thumbs down”. To determine this sentiment polarity, we propose a novel machine-learning method that applies text-categorization techniques to just the ..."
Abstract
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the subjective portions of the document. Extracting these portions can be implemented using efficient techniques for finding minimum cuts in graphs; this greatly facilitates incorporation of cross-sentence contextual constraints. Publication info: Proceedings of the ACL, 2004. 1
A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts
"... Sentiment analysis seeks to identify the viewpoint(s) underlying a text span; an example application is classifying a movie review as “thumbs up” or “thumbs down”. To determine this sentiment polarity, we propose a novel machine-learning method that applies text-categorization techniques to just the ..."
Abstract
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the subjective portions of the document. Extracting these portions can be implemented using efficient techniques for finding minimum cuts in graphs; this greatly facilitates incorporation of cross-sentence contextual constraints. 1
A Model of Investor Sentiment
- Journal of Financial Economics
, 1998
"... Recent empirical research in finance has uncovered two families of pervasive regularities: underreaction of stock prices to news such as earnings announcements, and overreaction of stock prices to a series of good or bad news. In this paper, we present a parsimonious model of investor sentiment, or ..."
Abstract
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Cited by 743 (28 self)
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Recent empirical research in finance has uncovered two families of pervasive regularities: underreaction of stock prices to news such as earnings announcements, and overreaction of stock prices to a series of good or bad news. In this paper, we present a parsimonious model of investor sentiment
Opinion Mining and Sentiment Analysis
, 2008
"... An important part of our information-gathering behavior has always been to find out what other people think. With the growing availability and popularity of opinion-rich resources such as online review sites and personal blogs, new opportunities and challenges arise as people now can, and do, active ..."
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Cited by 711 (3 self)
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, actively use information technologies to seek out and understand the opinions of others. The sudden eruption of activity in the area of opinion mining and sentiment analysis, which deals with the computational treatment of opinion, sentiment, and subjectivity in text, has thus occurred at least in part
A Trainable Document Summarizer
, 1995
"... To summarize is to reduce in complexity, and hence in length, while retaining some of the essential qualities of the original. This paper focusses on document extracts, a particular kind of computed document summary. ..."
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Cited by 525 (2 self)
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To summarize is to reduce in complexity, and hence in length, while retaining some of the essential qualities of the original. This paper focusses on document extracts, a particular kind of computed document summary.
Sentiments ∗
, 2012
"... This paper shows how extrinsic fluctuations, and forces akin to “animal spirits”, can be accommodated in unique-equilibrium, rational-expectations, macroeconomic models like those in the RBC/DSGE paradigm. To this goal, we limit the communication that is embedded in a neoclassical economy by letting ..."
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Cited by 3 (0 self)
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by letting trading be random and decentralized. We then show that, as long as this prevents agents from reaching identical equilibrium expectations, these expectations, and macroeconomic outcomes, may vary with a certain type of extrinsic shocks which we call “sentiments”. These shocks are akin to sunspots
Determining the sentiment of opinions
- In Proceedings of the 20th International Conference on Computational Linguistics (COLING’04
, 2004
"... Identifying sentiments (the affective parts of opinions) is a challenging problem. We present a system that, given a topic, automatically finds the people who hold opinions about that topic and the sentiment of each opinion. The system contains a module for determining word sentiment and another for ..."
Abstract
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Cited by 286 (5 self)
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Identifying sentiments (the affective parts of opinions) is a challenging problem. We present a system that, given a topic, automatically finds the people who hold opinions about that topic and the sentiment of each opinion. The system contains a module for determining word sentiment and another
Lexicon-Based Methods for Sentiment Analysis
"... We present a lexicon-based approach to extracting sentiment from text. The Semantic Orientation CALculator (SO-CAL) uses dictionaries of words annotated with their semantic orientation (polarity and strength), and incorporates intensification and negation. SO-CAL is applied to the polarity classific ..."
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Cited by 167 (13 self)
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We present a lexicon-based approach to extracting sentiment from text. The Semantic Orientation CALculator (SO-CAL) uses dictionaries of words annotated with their semantic orientation (polarity and strength), and incorporates intensification and negation. SO-CAL is applied to the polarity
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