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Here is a simple Naive Bayes test data
# positive or negative, whether it contains word a1, wether it contains word a2, ....
0,1 0 0
0,1 0 0
1,0 1 0
1,0 1 0
So we need to have
1. Find a list of impo…
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I, as a user, need to be able to save tweets classified as relevant to a data store in MySQL.
Data Elements
tweet_time
unique_tweet_id
analysis_name
tweeter
tweeter_screen_name
tweet_text…
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**Coach assistant:** @probeadd
**Sanity checks:**
* [x] GitHub profile photo + detailed profile description
**Organizations:**
1. CLiPS, University of Antwerp
2. Stony Brook Univers…
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@huyxmai Please run the LSTM classifier in the following way:
1) Train on old dataset and validate on new dataset
* Compare the results of training the relevance classifier with english tweets …
ghost updated
3 years ago
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### AAG Paper Tasks
- [x] Mine additional tweets until present
- [x] Frequency analysis of nouns, adjectives, noun phrases
- [x] Sentiment analysis with EmoLex
- [x] Select tweets scoring ab…
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- [x] - Write code to acces the saved twitter data and load all variables
- [x] - open data files containing tweet information
- [x] - download/import pre-made datasets including only geotagg…
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Combine all tweets from each user who self-identifies as suffering from chronic pain conditions. Strip out references to the conditions. Can a patient's condition be inferred via cluster analysis or o…
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My primary concern with the current dataset (i.e. the data in `fetched_tweets.txt`) is that 90% of the Tweets concern Donald Trump. So, it seems like any analysis / visualizations we do will be prima…
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I think this can be an opportunity to tune the bot.
Would it be possible to create an analysis of the regex's and the number of tweets they captures? With this information we can identify the regex's…
ghost updated
7 years ago
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Currently it only shows sentimental analysis of user's tweets. Is it possible to implement hastags or topics?
Thanks!