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Sentiment analysis

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Lucia Popadič

on 10 March 2013

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Transcript of Sentiment analysis

BASIC introduction Extremely simple
process explanation 1) define words your program should distinguish or how to know what people mean Sentiment analysis Business stuff new product perception
brand perception
reputation management
flame detection Individual usage? WITHOUT reading! every. single. post what is it? software what is it FOR? extracting opinions, sentiments, emotions who can use it? sellers, movie makers, anyone What can be analyzed? facts opinions MacBook is more expensive than Asus I so love Apple products! reviews
newspaper articles
discussions I want to: buy something
go somewhere
use a service
watch movies
political issues SPAM FILTERING important mainly because of the words in the message What kind of text? Methods 1) naive bayes
2) decision tree they need to have certain value +0.85, -0.72 (here also colour) so the computer will recognize them

example: good FFF700
sh*t 00553A friend's bc.thesis
less than 3* - bad
3 and more * - good
training process
new review must be classified according to words not * THE MOST INTERESTING THING I'VE FOUND WEBPAGE Feeling (happy, sad, depressed, etc.)
Age (in ten year increments - 20s, 30s, etc.)
Gender (male or female)
Weather (sunny, cloudy, rainy, or snowy)
Location (country, state, and/or city)
Date (year, month, and/or day) The top 200 feelings were manually assigned colors that loosely correspond to the tone of the feeling. Happy positive feelings are bright yellow. Sad negative feelings are dark blue. Angry feelings are red. Calm feelings are green Do Europeans feel sad more often than Americans? Do women feel fat more often than men? Does rainy weather affect how we feel? What are the most representative feelings of female New Yorkers in their 20s? What do people feel right now in Baghdad? What were people feeling on Valentine's Day? Which are the happiest cities in the world? The saddest? And so on... Madness Mobs I feel... RELIEVED that it's over now. thank you for your attention. Lucia Popadicova 1ES References:
Ján Hresko, student of TUKE wefeelfine.org 2) divide them - positive/negative 3) make the program learn positive and negative words 4) find the text you want to analyze 5) let the program work and figure out polarity
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