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- Kristina Lerman, Rumi Ghosh, Jeon-Hyung Kang
- MLG@KDD
- 2010
Centrality is an important notion in network analysis and is used to measure the degree to which network structure contributes to the importance of a node in a network. While many different… (More)
The structure of a social network contains information useful for predicting its evolution. We show that structural information also helps predict activity. People who are "close" in some sense in a… (More)
- Jihie Kim, Jeon-Hyung Kang
- Applied Intelligence
- 2010
Online discussion is a popular form of web-based computer-mediated communication and is a dominant medium for cyber communities in areas of information sharing, customer support and distributed… (More)
The emergence of social media creates a unique opportunity for developing a new class of crowd-powered information collection systems. Such systems actively identify potential users based on their… (More)
- Jeffrey Nichols, Jeon-Hyung Kang
- CSCW
- 2012
When people have questions, they often turn to their social network for answers. If the answer is obscure or time sensitive however, no members of their social networks may know the answer. For… (More)
- Jeon-Hyung Kang, Kristina Lerman, Anon Plangprasopchok
- SOMA@KDD
- 2010
Recently, there has been a great deal of interest in analyzing inherent structures in posts on microblogs such as Twitter. While many works utilize a well-known topic modeling technique, we instead… (More)
- Jeon-Hyung Kang, Kristina Lerman, Lise Getoor
- SBP
- 2013
Social media users have finite attention which limits the number of incoming messages from friends they can process. Moreover, they pay more attention to opinions and recommendations of some friends… (More)
- Jeon-Hyung Kang, Jun Ma, Yan Liu
- SDM
- 2012
The increasing volume of short texts generated on social media sites, such as Twitter or Facebook, creates a great demand for effective and efficient topic modeling approaches. While latent Dirichlet… (More)
- Kristina Lerman, Prachi Jain, Rumi Ghosh, Jeon-Hyung Kang, Ponnurangam Kumaraguru
- 2013 International Conference on Social…
- 2013
How does one find important or influential people in an online social network? Researchers have proposed a variety of centrality measures to identify individuals that are, for example, often visited… (More)
- Jeon-Hyung Kang, Kristina Lerman
- AAAI
- 2013
Probabilistic models can learn users’ preferences from the history of their item adoptions on a social media site, and in turn, recommend new items to users based on learned preferences. However,… (More)