# General configuration

# Network settings
network_type = 1
number_of_nodes = 1000
max_time = 50
num_trials = 1
timeout = 2

# Zombie model
bite_prob = 0.01  # 0-1
heal_prob = 0.01  # 0-1

# Bass model
innovation_prob = 0.001
imitation_prob = 0.005

# Sentiment Correlation model
outside_effects_prob = 0.2
anger_prob = 0.06
joy_prob = 0.05
sadness_prob = 0.02
disgust_prob = 0.02

# Big Market model
## Names
enterprises = ["BBVA", "Santander", "Bankia"]
## Users
tweet_probability_users = 0.44
tweet_relevant_probability = 0.25
tweet_probability_about = [0.15, 0.15, 0.15]
sentiment_about = [0, 0, 0]  # Default values
## Enterprises
tweet_probability_enterprises = [0.3, 0.3, 0.3]

# SISa
neutral_discontent_spon_prob = 0.04
neutral_discontent_infected_prob = 0.04
neutral_content_spon_prob = 0.18
neutral_content_infected_prob = 0.02

discontent_neutral = 0.13
discontent_content = 0.07
variance_d_c = 0.02

content_discontent = 0.009
variance_c_d = 0.003
content_neutral = 0.088

standard_variance = 0.055

# Spread Model M2 and Control Model M2
prob_neutral_making_denier = 0.035

prob_infect = 0.075

prob_cured_healing_infected = 0.035
prob_cured_vaccinate_neutral = 0.035

prob_vaccinated_healing_infected = 0.035
prob_vaccinated_vaccinate_neutral = 0.035
prob_generate_anti_rumor = 0.035