Lecture 3: Structuring Unstructured Texts Through Sentiment Analysis

MARINA SANTINI

P R O G R A M : C O M P U TAT I O N A L L I N G U I S T I C S A N D L A N G U A G E T E C H N O L O G Y

D E P T O F L I N G U I S T I C S A N D P H I L O L O G Y

UPPSALA UNIVERSITY, SWEDEN

21 NOV 2013

Semantic Analysis in Language Technology

Lecture 3 - Semantic-Oriented Applications:Sentiment Analysis

Course Website: http://stp.lingfil.uu.se/~santinim/sais/sais_fall2013.htm

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Acknowledgements

Thanks to Bing Liu for the many slides I borrowed from his Tutorial on Sentiment Analysis and Opinion Mining. Big thanks to Dan Jurafsky for his slides from Coursera NLP course.

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Why are sentiments important (opinions/emotions/affects/attitudes/etc)

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Text Categorization Problem

Different level of granularity: Document Sentence Summary

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Opionion: Formalization: Quadruple (4 components)

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Whatch out!

Date: The date is important in practice because one often wants to know how opinions change with time and opinion trends.

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Opionion: Formalization: Quintuple (5 components)

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In which way ”sentiment” belongs to semantics?

Semantics is the study of meaning: It focuses on the relation

between signifiers, like words, phrases, signs, and symbols, and what they stand for. Through a semantics, we want to understand human language.

Through SA we want to automatically identify the meaning of certain words, phrases, etc. and how they relate to affective states expressed in texts (long, short, oral, written, etc.)

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Subjectivity & Emotion

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Subjectivity

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Emotion

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Sentiment, Subjectivity, Emotion

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Affect and Affective words…

http://research.microsoft.com/en-us/projects/tweetaffect/

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Basically… Text Classification!

Topic-based classificationGenre identificationAuthorship attribution

(plagiarism, authorship/classification of anonymous texts)

Spam filtersAutomatic email classification

(folder assignment)Threat identificationEtc.

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Opinion Mining in the real world…

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UnSupervised Learning

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Supervised Classification

See Dan’s video presentation!

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Team Work: 20 min; Discussion 15 min

You are going to apply for funding . You are interested in Horizion 2020 funding scheme (the new European research and innovation funding framework)

You think it is a good idea to create a Mood Index App.

Plan with your team mates this new sentiment-based app. Present to the audience the following aspects:

1) Purpose: what is the main use of this new app? (ex, identification of self-distructive behavior, depressive states, sad/happy mood, freindly attitudes, etc.)

2) Target users: who is going to use this app? (young people, parents, etc)3) Scenario: describe a typical scenario/context where your app is going to be used with

fruitful results4) Computational aspects: Which sentiment classes is the app going to identify? In which

language? Which computational model is going to be based upon?5) The actors: what kind of experts do you need? (ex a computational linguist, a app

developer, a psychiatrist, a company taking care of marketing and commercialization, a social worker, school teacher etc.)

6) Societal Benefits: How can the commercialization of your app contribute to decrease unemployment in your country and/or in EU.

7) Any additional aspect you might find relevant.

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How to build your own Twitter Sentiment Analysis Tool

http://blog.datumbox.com/how-to-build-your-own-twitter-sentiment-analysis-tool/

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This is the end… Thanks for your attention !