dc.contributor
Technische Universität München
dc.contributor
Groh, Georg
dc.contributor.author
Xue, Zhouyang
dc.date.issued
2016-12-15
dc.identifier
https://hdl.handle.net/2117/101956
dc.description.abstract
The current work collected a dataset on the interaction between people to be used in
future research on sentiment analysis. Based on messages sent from an individual to
others, a crawler is build to able to identify individual with high likelihood of response.
Based on a random forest model that analyzes features in message and frequent term
count analysising the text body, the crawler was able to detect replyied individuals
with 75% of acurracy. This allowed us to build a dense and strong connected social
network and thus can works for more detailed analysis social researches.
dc.format
application/pdf
dc.publisher
Universitat Politècnica de Catalunya
dc.subject
Àrees temàtiques de la UPC::Informàtica
dc.subject
Machine learning
dc.subject
Aprenentatge automàtic
dc.subject
Mineria de dades
dc.title
Targeted data enrichment for an existing large sparse dataset
