Data Analytics for Social Network Marketing

Influencer marketing is a new and innovative way for brands to target their customers on social media in a highly accurate and trusted way. Brand partners work with hundreds of influencers over a period of time, which is called a campaign, to create marketing material. This marketing material is shared by both the brand and influencer to the audience of the influencers, who are followers on social networking platforms such blogs, YouTube, Instagram, and Facebook. A key challenge in influencer marketing is to identify influencers with the greatest social networking reach. This project will develop machine learning and data analytics methods based on natural language processing to automatically and accurately match identify influencers for brands.

Faculty Supervisor:

Alexander Rutherford

Student:

Milad Toutounchian

Partner:

MuseFind

Discipline:

Engineering

Sector:

Information and communications technologies

University:

Program: