Predicting and Interpreting Bipartite Temporal Networks

A network, is defined as a collection of nodes interconnected by links. When this topology changes through time, we call it a temporal network. A specific class of networks, with only two types of nodes with no connections between one kind, is the bipartite network. An example is a telecommunications network, where nodes represent...

Stock market prediction using social media data and finding the covariance of the LASSO

Stock market prediction has been a research topic for decades; recently, efforts to increase the accuracy by including data from social media like Google and Twitter received a lot of attention. Social media can be regarded as indicator for sentiments and sentiments are known to influence the stock market. Current models lack interpretation; it...

Social Media Aided Stock Market Predictions by Sparsity Induced Regression

Prediction of the stock market has been a research topic for decades. Recently, data from social media like Google and Twitter are included in prediction models. This data serves as an indicator of sentiments that are potentially useful for prediction. Interpretation of current prediction methods is cumbersome. Beforehand it is not known which...