Editing The Sociology of Networks (section)

== <span style="color: #FFFFFF;">Applying</span> ==
'''Modeling 'The Social Capital' (Measuring a person's 'Wealth' in connections):'''
<syntaxhighlight lang="python">
def estimate_social_capital(num_close_friends, num_acquaintances):
    """
    Shows the balance between 'Support' and 'Opportunity'.
    """
    # Bonding = Deep support
    bonding_score = num_close_friends * 10
    # Bridging = New opportunities
    bridging_score = num_acquaintances * 5
    
    if bonding_score > 50 and bridging_score > 50:
        status = "WELL-CONNECTED: Balanced life."
    elif bonding_score > 50:
        status = "BONDED BUT ISOLATED: High support, Low opportunity."
    else:
        status = "THE LADDER-CLIMBER: High opportunity, Low support."
        
    return f"Capital: {bonding_score + bridging_score} | {status}"

# Case: Someone with 3 best friends and 50 acquaintances
print(estimate_social_capital(3, 50))
</syntaxhighlight>

; Sociology Landmarks
: '''The 'Milgram' Small World Study (1967)''' → Proved that the "Human Web" is surprisingly "Tight," with only "6 steps" between a "Farmer in Nebraska" and a "Stranger in Boston."
: '''The 'Bennington' College Study''' → How "Friends" change your "Politics." Students who entered a conservative college became "Liberal" because their "Social Network" was liberal.
: '''Dunbar's Number (150)''' → The "Biological Limit" of our networks. Our brains are only built to handle "150 meaningful relationships." If your network is bigger, it becomes "Impersonal."
: '''The 'Rich-Get-Richer' Effect (Matthew Effect)''' → In networks, the people who "Already have many friends" are the ones who "Get the most new friends," leading to "Extreme Inequality" in social power.
</div>

<div style="background-color: #8B4500; color: #FFFFFF; padding: 20px; border-radius: 8px; margin-bottom: 15px;">