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Accession Number ADA589957
Title Learning for Microblogs with Distant Supervision: Political Forecasting with Twitter.
Publication Date Apr 2012
Media Count 11p
Personal Author M. Marchetti-Bowick N. Chambers
Abstract Microblogging websites such as Twitter offer a wealth of insight into a population's current mood. Automated approaches to identifying general sentiment toward a particular topic often perform two steps: Topic Identification and Sentiment Analysis. Topic Identification identifies tweets that are relevant to a desired topic (e.g., a politician or event), and Sentiment Analysis extracts each tweet's attitude toward the topic. Many techniques for Topic Identification simply involve selecting tweets using a keyword search. Here we present an approach that uses distant supervision to train a classifier on the tweets returned by the search. We show that distant supervision leads to improved performance in the Topic Identification task as well as in the downstream Sentiment Analysis task. We then use a system that incorporates distant supervision into both stages to analyze sentiments toward President Obama as expressed in a dataset of tweets. That is, we apply our approach to the problem of predicting Presidential Job Approval polls from Twitter data. Our results show better correlation with Gallup's Presidential Job Approval polls than previous work. We also present a novel baseline that performs remarkably well without using Topic Identification.
Keywords Attitudes(Psychology)
Classification
Computational linguistics
Distant supervision
Emotions
Forecasting
Identification
Internet
Keyword selection
Learning machines
Microblogs
Online communities
Opinion analysis
Political forecasting
Political sentiment
Political tweets
Predictions
Public opinion
Sentiment analysis
Sentiment classification
Social media
Social networks
Symposia
Text processing
Topic identification
Training
Twitter
Words(Language)


 
Source Agency Non Paid ADAS
NTIS Subject Category 92D - Education, Law, & Humanities
92B - Psychology
57T - Psychiatry
62 - Computers, Control & Information Theory
Corporate Author Naval Academy, Annapolis, MD. Dept. of Computer Science.
Document Type Technical report
Title Note Conference paper.
NTIS Issue Number 1409
Contract Number N/A

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