Skip to main navigation
Skip to search
Skip to main content
University of Birmingham Home
Help & FAQ
Link opens in a new tab
Search content at University of Birmingham
Home
Research output
Profiles
Research units
Projects
Activities
Datasets
Equipment
Prizes
Press/Media
A dynamic bibliometric model for identifying online communities
[No Value] [No Value]
,
Ata Kaban
Computer Science
Research output
:
Contribution to journal
›
Article
6
Citations (Scopus)
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'A dynamic bibliometric model for identifying online communities'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Community Identification
100%
Online Communities
100%
Distinctive Features
50%
Markov
50%
Generative Models
50%
Temporal Delay
50%
Timing Analysis
50%
Predictive Modeling
50%
Memory Length
50%
Community Structure
50%
Communication Technologies
50%
Online Interaction
50%
User Interaction
50%
Computationally Efficient
50%
Temporal Events
50%
State Clustering
50%
Dynamic Users
50%
Computer-mediated Interaction
50%
Network Connection
50%
Clustering Methodology
50%
Internet Relay Chat
50%
Historical Data Analysis
50%
Maximum Likelihood Estimation Algorithm
50%
Online Dynamics
50%
Online Communication
50%
Computer Science
maximum-likelihood
100%
Estimation Algorithm
100%
Chat
100%
Likelihood Estimation
100%
Incremental Version
100%
Generative Model
100%
Structural Aspect
100%
Network Connection
100%
User Interaction
100%
Historical Data
100%
Distinctive Feature
100%
Information Technology
100%
Online Communities
100%