2015-12-04 10:41:42 +00:00
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# settings.py
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def init():
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global number_of_nodes
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global max_time
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global num_trials
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global bite_prob
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global network_type
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global heal_prob
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global innovation_prob
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global imitation_prob
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global timeout
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global outside_effects_prob
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global anger_prob
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global joy_prob
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global sadness_prob
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global disgust_prob
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2015-12-17 11:56:39 +00:00
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global tweet_probability_users
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global tweet_relevant_probability
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global tweet_probability_about
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global sentiment_about
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global tweet_probability_enterprises
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2016-04-13 16:08:41 +00:00
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global enterprises
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2015-12-04 10:41:42 +00:00
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network_type=1
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2016-04-13 16:08:41 +00:00
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number_of_nodes=50
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max_time=500
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2015-12-04 10:41:42 +00:00
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num_trials=1
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2016-04-13 16:08:41 +00:00
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timeout=1
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2015-12-04 10:41:42 +00:00
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#Zombie model
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bite_prob=0.01 # 0-1
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heal_prob=0.01 # 0-1
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#Bass model
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2016-04-13 16:08:41 +00:00
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innovation_prob=0.001
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imitation_prob=0.005
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2015-12-04 10:41:42 +00:00
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2015-12-17 11:56:39 +00:00
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#Sentiment Correlation model
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2015-12-04 10:41:42 +00:00
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outside_effects_prob = 0.2
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2016-04-13 16:08:41 +00:00
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anger_prob = 0.06
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2015-12-04 10:41:42 +00:00
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joy_prob = 0.05
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sadness_prob = 0.02
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disgust_prob = 0.02
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2015-12-17 11:56:39 +00:00
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#Big Market model
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2016-04-13 16:08:41 +00:00
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##Names
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enterprises = ["BBVA","Santander", "Bankia"]
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2015-12-17 11:56:39 +00:00
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##Users
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tweet_probability_users = 0.44
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tweet_relevant_probability = 0.25
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2016-04-13 16:08:41 +00:00
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tweet_probability_about = [0.15, 0.15, 0.15]
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sentiment_about = [0, 0, 0] #Valores por defecto
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2015-12-17 11:56:39 +00:00
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##Enterprises
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2016-04-13 16:08:41 +00:00
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tweet_probability_enterprises = [0.3, 0.3, 0.3]
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2015-12-17 11:56:39 +00:00
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