Social Media Analytics for Research Insights Training Course

Social Media Analytics for Research Insights Training Course

Introduction

In the digital age, social media analytics has emerged as a powerful tool for extracting real-time insights, identifying emerging trends, and understanding public sentiment across platforms like Twitter, Facebook, LinkedIn, TikTok, and Instagram. Social Media Analytics for Research Insights Training Course empowers participants to leverage data-driven methods to monitor conversations, uncover behavioral patterns, and generate actionable insights that influence decision-making across industries. The training is designed for professionals seeking to enhance their data literacy, integrate AI-powered analytics tools, and harness sentiment analysis, influencer tracking, and engagement metrics to gain competitive intelligence.

As organizations prioritize digital transformation, the ability to mine big social data, utilize natural language processing (NLP), and apply predictive analytics is essential for researchers, marketers, and policy analysts. This course blends theoretical foundations with hands-on practice using leading social media intelligence platforms and open-source tools. Participants will engage in case studies, scenario-based simulations, and peer-reviewed projects to build proficiency in turning complex, unstructured social media data into evidence-based reports, predictive models, and strategic communication frameworks.

Course Objectives

1. Understand the fundamentals of social media analytics and digital listening.
2. Apply sentiment analysis and emotion detection to social conversations.
3. Use social network analysis (SNA) to identify influencers and communities.
4. Leverage big data tools for large-scale social media mining.
5. Utilize hashtag tracking and keyword mapping for research purposes.
6. Conduct comparative analysis across multiple platforms (Twitter, Facebook, Instagram, etc.).
7. Implement predictive analytics for trend forecasting in social media.
8. Employ NLP techniques for extracting topics, entities, and opinions.
9. Create real-time dashboards and visualizations with analytics software.
10. Analyze misinformation, disinformation, and bot behavior.
11. Extract behavioral insights from video-based and visual social content.
12. Apply ethics and privacy principles in social media data collection.
13. Design research-based social media campaigns and evaluations..

Target Audiences

1. Academic Researchers
2. Digital Marketing Professionals
3. Policy Analysts and Think Tanks
4. Journalists and Media Analysts
5. NGO and Advocacy Professionals
6. Corporate Communication Teams
7. Government and Public Sector Officials
8. Data Scientists and IT Analysts

Course Duration: 5 days

Course Modules

Module 1: Introduction to Social Media Analytics

• Importance of social media data in research
• Types of social media data: structured vs. unstructured
• Key metrics and KPIs for social analytics
• Overview of tools and platforms
• Ethical concerns in social data use
• Case Study: Mapping COVID-19 discourse on Twitter

Module 2: Sentiment and Emotion Analysis

• Sentiment classification: positive, neutral, negative
• Emotion tracking using machine learning
• Comparison of sentiment tools (e.g., VADER, TextBlob, Azure ML)
• Practical sentiment analysis in Python or R
• Using sentiment insights for audience profiling
• Case Study: Sentiment shifts during election campaigns

Module 3: Social Network and Influencer Analysis

• Introduction to Social Network Analysis (SNA)
• Metrics: centrality, modularity, clustering
• Identifying influencers and opinion leaders
• Visualizing social networks with Gephi or NetworkX
• Measuring influence vs. popularity
• Case Study: Influencer network around environmental activism

Module 4: Hashtag and Keyword Tracking

• Identifying trending hashtags and keywords
• Temporal analysis of tag use
• Semantic clustering of hashtags
• Topic modeling (LDA, NMF) for keyword grouping
• Platform-specific trends (TikTok vs Twitter)
• Case Study: Hashtag movements in gender-based violence campaigns

Module 5: Platform-Specific Analytics

• Twitter API and X data collection
• Facebook Audience Insights and Meta Ads Library
• Instagram analytics and visual content mining
• TikTok trend tracking and engagement analysis
• Cross-platform data integration techniques
• Case Study: Tracking misinformation across platforms

Module 6: Visualization and Dashboarding

• Tools: Power BI, Tableau, Google Data Studio
• Designing real-time social dashboards
• Data storytelling and infographic reporting
• Custom dashboards for clients/stakeholders
• Mapping geographic trends
• Case Study: Live dashboard for disaster response monitoring

Module 7: Predictive and Behavioral Analytics

• Predicting virality using engagement metrics
• Trend forecasting models
• Behavioral segmentation of audiences
• Temporal and geospatial analytics
• Integrating Google Trends and web search data
• Case Study: Predicting vaccine hesitancy via behavioral patterns

Module 8: Ethics, Privacy & Strategic Application

• GDPR, consent, and anonymization
• Bias and algorithmic fairness in social data
• Designing ethical research protocols
• Social media for good: advocacy and change
• Evaluation metrics for impact assessment
• Case Study: Ethical framework for crisis communication research

Training Methodology

• Interactive lectures and multimedia presentations
• Tool-based demonstrations (Twitter API, Gephi, Tableau, etc.)
• Hands-on exercises and real-time data projects
• Peer-reviewed group case studies
• Guided simulations using open-source datasets
• Personalized feedback and strategic planning sessions

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104 

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

 We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.