Sentiment Analysis and Predictive Models

Moleskine’s philosophy is culture, travel, memory, imagination and personal identity. The goal of this project is to find influencers by looking at users' interactions and to target them across different social platforms. For example, we will look at how people connect in Twitter and create a weighted graph using both following numbers and @mentions. We will look at all platforms and cluster groups of posts by trending topics using LDA. This can be applied to all sources of media. We will then try to identify if trending topics and influencers are common across social platforms.

Also we will apply reverse engineering using the Leuchtrum case. What were the influencers doing before being sponsored by the company? The project will explore the popularity and success of different Moleskine products co-branded with other famous brands (also known as special editions) and launched during specific periods of time. The main field of analysis is measuring the impact of different products on social media channels and correlating that to sales.

 

See also: Moleskine, 2017