Social Media Mining

Course Objective

To provide a strong foundation in social media mining, understand the importance of social media mining and learn how to gain advantage from it for business development

Learning Outcomes

Upon completion of this course, students will be able to

Search on social media more effectively

Accessing product reviews and retrieving data from various social media platforms

Analyse data from data from social media and provide relevant information for business development

Detailed Syllabus

  1. Introduction: Importance of social media mining, Basics of social media mining, Social media mining techniques, Basic data mining algorithms, Opinion mining
  2. Discussions on Various Social Media Platforms: Email, chat, media sharing, blogs, micro blogs, social news, social book marking, professional groups, community based questions and answers and wikis
  3. Potentials and Pitfalls of Social Media Data: Opinion mining made difficult, Sentiment and its measurement, The nature of social media data, Traditional versus non traditional social data, measurement and inferential challenges
  4. Social Media Mining Fundamentals: Key concepts of social media mining, Good data versus bad data, Understanding sentiments, Scherer’s typology of emotions, Sentiment polarity – data and classification, Supervised social media mining – lexicon-based sentiment , Supervised social media mining – Naive Bayes classifiers, Unsupervised social media mining – Item Response Theory for text scaling
  5. More on Social Media: Searching on social media, Accessing product review from the sites, Retrieving data from Wikipedia, Using the Tumbler API, Accessing data from Quora, Mapping solutions using Google maps, Professional network data from LinkedIn, Getting blogger data, Retrieving data from Foursquare, Yelp and other networks