About the Journal

Journal Name : Social Media Computing  

Inicial : SMC  
Abbreviation : Soc. Med. Com  
Publish Time : Four issues a year | January, April, July, and October  
DOI : -  
e-ISSN : -  
Editor-in-Chief : Assoc. Prof. Dr. Aang Subiyakto  
Publisher : Social Computing Research Institute  
Social Media Computing is an academic journal which focus on to the intersection of social media platforms and computational techniques used to analyze, enhance, or optimize social interactions, content, and networks. It involves various fields, including data science, artificial intelligence (AI), machine learning (ML), network analysis, and human-computer interaction (HCI). 

Social Media Computing (SMC) is an international, open-access, peer-reviewed journal that focuses on analysing, managing, and developing technologies related to social media. SMC is interested in research not only on information technology, data analysis, artificial intelligence, and social sciences but also on new trends and developments, Social Media Data Analysis, Content Algorithms and Personalization, Information Dissemination and Misinformation, Security, Privacy, and Ethics in Social Media, Social and Psychological Impact of Social Media. SMC is published four times yearly: in January, April, July, and October. Each article is reviewed by two blind reviewers from an internationally recognised pool of reviewers.

Social Media Computing is an academic journal which focus on to the intersection of social media platforms and computational techniques used to analyze, enhance, or optimize social interactions, content, and networks. It involves various fields, including data science, artificial intelligence (AI), machine learning (ML), network analysis, and human-computer interaction (HCI).

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
      This work is licensed under a Creative Commons Attribution-ShareAlike 4.0

This Journal indexed by :