Computer • Chapter 21

Social Networking

सोशल नेटवर्किंग
Evolution • Architecture • Data Flow • Algorithms • Feed Ranking • ML • Security • Popular Sites
Social Networking / सोशल नेटवर्किंग
  • Social Networking is described as a technology-driven system that enables users to create digital identities, establish social connections, generate content and interact through algorithm-controlled platforms using internet-based services.
हिंदी सार
सोशल नेटवर्किंग एक तकनीक-आधारित प्रणाली है जिसमें उपयोगकर्ता डिजिटल पहचान बनाते हैं, सामाजिक संबंध स्थापित करते हैं, कंटेंट तैयार करते हैं और एल्गोरिदम-नियंत्रित प्लेटफॉर्म के माध्यम से संवाद करते हैं।

Identity

Digital profile / पहचान

Connections

Social relationships / सामाजिक संबंध

Content + Algorithms

Content creation and algorithm-controlled delivery.

Evolution of Social Networking
Evolution of social networking
Source-derived timeline using the exact phases and descriptions listed in the PDF.
PhasePlatformDescription in Source
1997SixDegreesFirst social networking site
2002FriendsterFriend-based networking
2004FacebookProfile + Feed system
2006TwitterMicroblogging
2010+Instagram, WhatsAppMedia-centric networking
Technical Architecture / तकनीकी संरचना
Social networking architecture
Five core layers exactly as organized in the source.
LayerSource Examples / Role
User Interface Layer (UI)Profile, Feed, Buttons
Application LayerBusiness logic, API
Algorithm LayerRanking, Recommendation
Database LayerUser data, Posts
Network LayerInternet, CDN
Data Flow / डेटा कैसे चलता है?
Social networking data flow
Source-derived 7-step flow. The PDF calls the final cycle a Feedback Loop System.
  1. User uploads content.
  2. Content is stored in the database.
  3. Algorithm analyzes content.
  4. Ranking is applied.
  5. Feed is generated.
  6. User interaction is recorded.
  7. Feedback improves the algorithm.
Social Networking Algorithm

A Social Networking Algorithm is defined in the source as a set of rules and AI models that decides what content a user sees, when, and how often.

AlgorithmFunction in Source
Ranking AlgorithmDetermines order of posts
Recommendation AlgorithmFriend/video suggestions
Engagement AlgorithmMeasures likes and comments
Filtering AlgorithmRemoves spam
Advertisement AlgorithmTargeted Ads
Feed Ranking / फीड रैंकिंग
Feed ranking factors
Main ranking factors listed in the source.
FactorExplanation
Affinity ScoreUser relationship strength
WeightType of content — source gives “video > image”
Time DecayNew posts get priority
Engagement RateLikes, shares, comments
RelevanceUser interest matching
Source Summary
Post priority depends on user interest, relationship, time and interaction. The source states: more interaction = more reach.
Machine Learning in Social Networking
  • Machine Learning analyzes user behavior to personalize content.
  • Uses listed in the source: Personalized Feed, Fake Account Detection, Sentiment Analysis, Trend Prediction.
AI / ML ModelUse in Source
Collaborative FilteringRecommendation
NLPText understanding
Computer VisionImage/Video
Deep LearningVideo ranking
Graph AlgorithmsSocial network
Security & Privacy / सुरक्षा व गोपनीयता
Security and cyber crimes
Source-derived security/cyber-crime visual.
Education & Business Uses

Education

Social networking supports online learning and collaboration.

  • YouTube
  • Google Classroom
  • WhatsApp
  • Telegram

Business

  • Brand Promotion
  • Digital Marketing
  • Customer Support
  • Feedback Collection
  • Influencer Marketing
Popular Social Networking Sites — Developed Year & Founder
Social SiteDeveloped YearFounder(s) — Source
Facebook2004Mark Zuckerberg
Instagram2010Kevin Systrom, Mike Krieger
Twitter (X)2006Jack Dorsey, Biz Stone, Evan Williams
LinkedIn2002Reid Hoffman
WhatsApp2009Jan Koum, Brian Acton
YouTube2005Chad Hurley, Steve Chen, Jawed Karim
Snapchat2011Evan Spiegel, Bobby Murphy
Telegram2013Pavel Durov
Pinterest2010Ben Silbermann
Reddit2005Steve Huffman, Alexis Ohanian
Quora2009Adam D’Angelo, Charlie Cheever
TikTok2016Zhang Yiming
Source Fidelity
Years and founder names above are reproduced from the PDF chapter as-is. No outside corrections or additions were made.
Quick Recall / त्वरित पुनरावृत्ति
One-Line Revision
  • Social Networking: digital identity + social connections + content + algorithm-controlled interaction.
  • Evolution: SixDegrees (1997) → Friendster (2002) → Facebook (2004) → Twitter (2006) → Instagram/WhatsApp (2010+).
  • Architecture: UI → Application → Algorithm → Database → Network.
  • Data Flow: Upload → Store → Analyze → Rank → Feed → Record interaction → Feedback improves algorithm.
  • Feedback Loop System: user response helps improve the algorithm.
  • Algorithms: Ranking • Recommendation • Engagement • Filtering • Advertisement.
  • Feed Factors: Affinity • Weight • Time Decay • Engagement • Relevance.
  • ML Uses: Personalized Feed • Fake Account Detection • Sentiment Analysis • Trend Prediction.
  • AI Models: Collaborative Filtering • NLP • Computer Vision • Deep Learning • Graph Algorithms.
  • Security: Encryption • 2FA • Privacy Settings • Content Moderation • AI Monitoring.
  • Cyber Crimes: Phishing • Cyber Bullying • Identity Theft • Fake Profiles • Deepfake.
  • Education: YouTube • Google Classroom • WhatsApp • Telegram.
  • Business: Promotion • Marketing • Support • Feedback • Influencer Marketing.
Exam Traps
Architecture layer ≠ Algorithm type: “Algorithm Layer” is a system layer; Ranking/Recommendation/etc. are algorithm categories.
Affinity Score ≠ Engagement Rate: Affinity = relationship strength; Engagement = likes/shares/comments.
Source boundary: Page 219 starts “India’s Achievements in IT Field,” so it is not merged into this chapter.