Topic Analysis to Identify Communities
Publicerad
Författare
Typ
Examensarbete för masterexamen
Program
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
Abstract
Being able to detect communities in social networks can be an aid in understanding
trends, assist moderation efforts and build recommendation systems. In this paper
we explore the use of topic models for community detection by proposing two such
models, LDAC and LDACS, based off of Latent Dirichlet Allocation (LDA) [1] and
the Community Topic Model [8]. These models are compared to LDA and evaluated
on datasets collected from Twitter and Reddit. It is concluded that LDACS may
be a reasonable and simple model for community detection, but with further study
needed, and that LDAC gives some credence to utilizing both topics and communities
in a model, but does itself not produce sufficient results to weigh up for its
complexity, although training it on more data might remedy this.
Beskrivning
Ämne/nyckelord
topic analysis, community detection, community, topic, thesis, lda, ldac, ldacs, ctm.