Detecting Twitter topics using Latent Dirichlet Allocation
Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Latent Dirichlet Allocations is evaluated for its suitability when detecting topics in a stream of short messages limited to 140 characters. This is done by assessing its ability to model the incoming messages and its ability to classify previously unseen messages with known topics. The evaluation shows that the model can be suitable for certain applications in topic detection when the stream size is small enough. Furthermoresuggestions on how to handle larger streams are outlined.
Place, publisher, year, edition, pages
2016. , 48 p.
UPTEC IT, ISSN 1401-5749 ; 16001
Engineering and Technology
IdentifiersURN: urn:nbn:se:uu:diva-277260OAI: oai:DiVA.org:uu-277260DiVA: diva2:904196
Master of Science Programme in Information Technology Engineering
Magnani, MatteoNordén, Lars-Åke