Research Projects

Current Projects

• Influence and Marketing Campaigns

Anthony will be investigating what makes an influence campaign successful. He will do this by exploring past successful (and unsuccessful) marketing campaigns and attempting to identify elements of the campaigns that led to their success or failure.

• HAMR

The Hierarchical Analysis of Machine learning for Resources seeks to provide a planning framework based on the CRISP-DM for organizations to analyze how well Artificial Intelligence can be implemented to a specific business problem. This is being spearheaded by the combined efforts of Sid, Tom, Anthony, and Bill.

• Early Alert Resource: Forecasting topic virality with Twitter and Google Trends

Trevor and Aidan have been working in tandem with CIMS (https://poole.ncsu.edu/subgroup/cims/) to incorporate predictive analytics involving social media into a preexisting alert system. By analyzing Twitter and Google Trends data, the team has developed an analytical process utilizing various innovative statistical methods to predict future virality for virtually any topic. These statistical methods include natural language processing tools (topic clustering and sentiment analysis) specifically designed for short-text data, as well as an auto-regressive forecasting method that accurately predicts future values based on a combination of past values from social media and Trends.

Past Projects

• Bot Detection: Classification using Functional Data Analysis

 

• Elict Latent Features of Social Media Users through Causal State Models