Aims and Scope

Key Aspects of Social Media Computing

  1. Social Network Analysis (SNA)

    • Studies the relationships between users, influencers, and communities.
    • Uses graph theory to model and analyze networks.

  2. Sentiment Analysis & Opinion Mining

    • Uses natural language processing (NLP) to determine emotions in posts.
    • Helps brands understandpublic perception and user feedback.

  3. Recommendation Systems

    • Algorithms suggest content, friends, or ads based on user behavior.
    • Uses collaborative filtering, content-based filtering, and deep learning.

  4. Content Moderation & Fake News Detection

    • AI models identify spam, hate speech, or misinformation.
    • Combats cyberbullying, bot activity, anddeepfake content.

  5. Trend Prediction & Virality Analysis

    • Predicts what topics will trend based on engagement patterns.
    • Helps businesses and marketers plan viral campaigns.

  6. Influencer & Community Detection

    • Identifies key opinion leaders in social networks.
    • Useful for marketing, political campaigns, and advocacy.

  7. Social Bots & Automation

    • AI-driven accounts can engage with users or generate content.
    • Ethical concerns include misinformation and manipulation risks.

  8. Privacy & Security

    • Studies how personal data is shared andprotected.
    • Investigates threats like phishing, data breaches, and user profiling.

 

Social Media Computing
ISSN : XXXX-XXXX
Organized by : Faculty of Science and Technology Building, 3rd Floor, 1st Campus, Universitas Islam Negeri (UIN) Syarif Hidayatullah Jakarta Jl. Ir. H. Juanda No.95, Ciputat Timur, Kota Tangerang Selatan, Banten 15412, Indonesia. 
Website : https://scrinstitute.org/journal/index.php/smc/
Email : smc@scrinstitute.org
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