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67 lines
1.6 KiB
Python
67 lines
1.6 KiB
Python
# General configuration
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import json
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with open('settings.json', 'r') as f:
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settings = json.load(f)
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network_params = settings[0]
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environment_params = settings[1]
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'''
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environment_params = {
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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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'innovation_prob': 0.001,
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'imitation_prob': 0.005,
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# Sentiment Correlation model
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'outside_effects_prob': 0.2,
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'anger_prob': 0.06,
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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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# Big Market model
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## Names
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'enterprises': ["BBVA", "Santander", "Bankia"],
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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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'tweet_probability_about': [0.15, 0.15, 0.15],
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'sentiment_about': [0, 0, 0], # Default values
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## Enterprises
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'tweet_probability_enterprises': [0.3, 0.3, 0.3],
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# SISa
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'neutral_discontent_spon_prob': 0.04,
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'neutral_discontent_infected_prob': 0.04,
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'neutral_content_spon_prob': 0.18,
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'neutral_content_infected_prob': 0.02,
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'discontent_neutral': 0.13,
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'discontent_content': 0.07,
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'variance_d_c': 0.02,
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'content_discontent': 0.009,
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'variance_c_d': 0.003,
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'content_neutral': 0.088,
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'standard_variance': 0.055,
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# Spread Model M2 and Control Model M2
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'prob_neutral_making_denier': 0.035,
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'prob_infect': 0.075,
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'prob_cured_healing_infected': 0.035,
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'prob_cured_vaccinate_neutral': 0.035,
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'prob_vaccinated_healing_infected': 0.035,
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'prob_vaccinated_vaccinate_neutral': 0.035,
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'prob_generate_anti_rumor': 0.035
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}
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''' |