Twitter Sentiment Analysis
Mert Kahyaoğlu
Instructor: Assoc. Prof. Dr. Bekir Taner Dinçer
NLP Course Project
AIM OF THE PROJECT
The aim of the project is to determine how people are feeling when they share something on twitter.
For example;
“ I'm so happy today! ” => Positive
" I feel bad :( ” => Negative
ROAD MAP
1.Collect Tweets
- Tweets;
- from Twitter API
- using Tweepy Helper Library
- Requirements
- Twitter Developer Application for authantication
2.Clean Tweets
- Hashtags ( # )
- Remove;
- Mentions ( @ )
- Links ( http://.. )
- Retweets ( RT .. )
- Limit ( length(word) > 2 )
Have you heard ‘Galata’ by @cmylmz on #SoundCloud? https://soundcloud.com/cmylmz/galata
Have you heard ‘Galata’ ?
3. LABEL & ForMAT
- Emoticons ( 😃 )
- Label by;
- Adjectives ( "perfect, sad, .." )
- Textual Emoticons ( ":D" )
- ( "Weather is perfect today 😃", "positive" )
- Format;
- ( "Rain makes me sad 😞", "negative" )
4.EXTRACT FEATURES & TRAIN DATA
[ "feel", "amazing", "today", "the", "view", "amazing",... ]
"I feel amazing today!"
"The view is amazing!"
...
nltk.FreqDist(wordlist)
["love", "this", "car"] : positive
...
nltk.NaiveBayesClassifier
.train(training_set)
Training Set;
...
classifier
NAIVE BAYES EXAMPLE
Should we play when outlook is overcast ?
5.CLASSIFY
Improvements
- Populate more training data
- Try other classification algorithms
- User interface