aspect based sentiment analysis ppt and opinion mining and sentiment analysis ppt
Dr.DouglasPatton,United States,Teacher
Published Date:26-07-2017
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Sentiment
Analysis
What is Sentiment
Analysis?Dan Jurafsky
Positive or negative movie review?
• unbelievably disappointing
• Full of zany characters and richly applied satire, and some
great plot twists
• this is the greatest screwball comedy ever filmed
• It was pathetic. The worst part about it was the boxing
scenes.
2Dan Jurafsky
Google Product Search
• a
3Dan Jurafsky
Bing Shopping
• a
4Dan Jurafsky
Twitter sentiment versus Gallup Poll of
Consumer Confidence
Brendan O'Connor, Ramnath Balasubramanyan, Bryan R. Routledge, and Noah A. Smith. 2010.
From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series. In ICWSM-2010Dan Jurafsky
Twitter sentiment:
Johan Bollen, Huina Mao, Xiaojun Zeng. 2011.
Twitter mood predicts the stock market,
Journal of Computational Science 2:1, 1-8.
10.1016/j.jocs.2010.12.007.
6Dan Jurafsky
Bollen et al. (2011)
• CALM predicts
DJIA 3 days
later
• At least one
current hedge
fund uses this
algorithm
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CALM Dow JonesDan Jurafsky
Target Sentiment on Twitter
• Twitter Sentiment App
• Alec Go, Richa Bhayani, Lei Huang. 2009.
Twitter Sentiment Classification using
Distant Supervision
8Dan Jurafsky
Sentiment analysis has many other names
• Opinion extraction
• Opinion mining
• Sentiment mining
• Subjectivity analysis
9Dan Jurafsky
Why sentiment analysis?
• Movie: is this review positive or negative?
• Products: what do people think about the new iPhone?
• Public sentiment: how is consumer confidence? Is despair
increasing?
• Politics: what do people think about this candidate or issue?
• Prediction: predict election outcomes or market trends
from sentiment
10Dan Jurafsky
Scherer Typology of Affective States
• Emotion: brief organically synchronized … evaluation of a major event
• angry, sad, joyful, fearful, ashamed, proud, elated
• Mood: diffuse non-caused low-intensity long-duration change in subjective feeling
• cheerful, gloomy, irritable, listless, depressed, buoyant
• Interpersonal stances: affective stance toward another person in a specific interaction
• friendly, flirtatious, distant, cold, warm, supportive, contemptuous
• Attitudes: enduring, affectively colored beliefs, dispositions towards objects or persons
• liking, loving, hating, valuing, desiring
• Personality traits: stable personality dispositions and typical behavior tendencies
• nervous, anxious, reckless, morose, hostile, jealousDan Jurafsky
Scherer Typology of Affective States
• Emotion: brief organically synchronized … evaluation of a major event
• angry, sad, joyful, fearful, ashamed, proud, elated
• Mood: diffuse non-caused low-intensity long-duration change in subjective feeling
• cheerful, gloomy, irritable, listless, depressed, buoyant
• Interpersonal stances: affective stance toward another person in a specific interaction
• friendly, flirtatious, distant, cold, warm, supportive, contemptuous
• Attitudes: enduring, affectively colored beliefs, dispositions towards objects or persons
• liking, loving, hating, valuing, desiring
• Personality traits: stable personality dispositions and typical behavior tendencies
• nervous, anxious, reckless, morose, hostile, jealousDan Jurafsky
Sentiment Analysis
• Sentiment analysis is the detection of attitudes
“enduring, affectively colored beliefs, dispositions towards objects or persons”
1. Holder (source) of attitude
2. Target (aspect) of attitude
3. Type of attitude
• From a set of types
• Like, love, hate, value, desire, etc.
• Or (more commonly) simple weighted polarity:
• positive, negative, neutral, together with strength
4. Text containing the attitude
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• Sentence or entire documentDan Jurafsky
Sentiment Analysis
• Simplest task:
• Is the attitude of this text positive or negative?
• More complex:
• Rank the attitude of this text from 1 to 5
• Advanced:
• Detect the target, source, or complex attitude typesDan Jurafsky
Sentiment Analysis
• Simplest task:
• Is the attitude of this text positive or negative?
• More complex:
• Rank the attitude of this text from 1 to 5
• Advanced:
• Detect the target, source, or complex attitude typesSentiment
Analysis
What is Sentiment
Analysis?Sentiment
Analysis
A Baseline
AlgorithmDan Jurafsky
Sentiment Classification in Movie Reviews
Bo Pang, Lillian Lee, and Shivakumar Vaithyanathan. 2002. Thumbs up? Sentiment
Classification using Machine Learning Techniques. EMNLP-2002, 79—86.
Bo Pang and Lillian Lee. 2004. A Sentimental Education: Sentiment Analysis Using
Subjectivity Summarization Based on Minimum Cuts. ACL, 271-278
• Polarity detection:
• Is an IMDB movie review positive or negative?
• Data: Polarity Data 2.0:
• http://www.cs.cornell.edu/people/pabo/movie-review-dataDan Jurafsky
IMDB data in the Pang and Lee database
✓✗
when _star wars_ came out some twenty years “ snake eyes ” is the most aggravating
ago , the image of traveling throughout the stars kind of movie : the kind that shows so
has become a commonplace image . …+ much potential then becomes
unbelievably disappointing .
when han solo goes light speed , the stars change
to bright lines , going towards the viewer in lines it’s not just because this is a brian
that converge at an invisible point . depalma film , and since he’s a great
director and one who’s films are always
cool .
greeted with at least some fanfare .
_october sky_ offers a much simpler image–that of
and it’s not even because this was a film
a single white dot , traveling horizontally across
starring nicolas cage and since he gives a
the night sky . . . .
brauvara performance , this film is hardly
worth his talents . Dan Jurafsky
Baseline Algorithm (adapted from Pang
and Lee)
• Tokenization
• Feature Extraction
• Classification using different classifiers
• Naïve Bayes
• MaxEnt
• SVM
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