An object o is a product, person, event, organization, or topic. o is represented as
a hierarchy of components, sub-components, and so on. Each node represents a component and is associated with a set of attributes of the component.
An opinion is a quintuple (o, f, so, h, t), where
is a target object. f is a feature of the object o. so is the sentiment value of the opinion of the opinion holder h on feature f of object o at time t. h is an opinion holder. t is the time when the opinion is expressed
OPINION MINING AND SENTIMENT ANALYSIS
Given a set of evaluative text documents D that contain opinions (or sentiments) about an object, opinion mining aims to extract attributes and components of the object that have been commented on in each document d ∈ D and to determine whether the comments are positive, negative or neutral. Sentiment analysis is a ...view middle of the document...
frequency Presence is more important than frequency
Parts of speech Adjectives, adverbs, nouns, verbs Negation “I like this book” and “I don‟t like this book” Similar but opposite! „No‟ does‟nt imply a negation. “No wonder it is one of the best”
A FEW APPROACHES TO THE PROBLEM
WORDNET BASED APPROACH
Determine sentiments of adjectives in WordNet by measuring relative distance of the term from exemplars, such as “good” and “bad”.
The polarity orientation of a term t is measured as follows O(t) = [d(t, good) − d(t, bad)] / d(good, bad) where d() is a WordNet based relatedness measure
GRAPH BASED METHODS
A mincut of a weighted graph G(V,E) is a partitioning the vertices V into V1 and V2 such that sum of the edge weights of all edges between V1 and V2 is minimal
GRAPH BASED METHODS
Classify datapoints by partitioning the similarity graph such that it minimizes the number of similar points being labeled differently
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