• Publications
  • Influence
Asking questions of targeted strangers on social networks
TLDR
We explore the feasibility of answering questions by asking strangers by mining the public status updates posted on Twitter. Expand
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LA-CTR: A Limited Attention Collaborative Topic Regression for Social Media
TLDR
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. Expand
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Towards identifying unresolved discussions in student online forums
TLDR
This paper presents an approach for classifying student discussions according to a set of discourse structures, and identifying discussions with confusion or unanswered questions. Expand
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Analyzing the quality of information solicited from targeted strangers on social media
TLDR
We explore the quality of information solicited from Twitter users in the domain of product reviews, specifically reviews for a popular tablet computer and L.A.-based food trucks. Expand
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Recommending items to group of users using Matrix Factorization based Collaborative Filtering
TLDR
Group recommender systems are becoming very popular in the social web owing to their ability to provide a set of recommendations to a group of users . Expand
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Centrality metric for dynamic networks
TLDR
We address this problem by introducing a novel centrality metric for dynamic network analysis that exploits an intuition that in order for one node in a dynamic network to influence another over some period of time, there must exist a path that connects the source and destination nodes through intermediaries at different times. Expand
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Using proximity to predict activity in social networks
TLDR
We use network proximity to capture the degree to which people are "close" to each other in a social network. Expand
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Transfer Topic Modeling with Ease and Scalability
TLDR
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. Expand
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Analyzing microblogs with affinity propagation
TLDR
We propose to apply Affinity Propagation [4] (AP) to analyze such a corpus, and we hypothesize that AP may provide different perspective to the traditional approach. Expand
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LA-LDA: A Limited Attention Topic Model for Social Recommendation
TLDR
We propose $\mathcal LA$ -LDA, a latent topic model which incorporates limited, non-uniformly divided attention in the diffusion process by which opinions and information spread on the social network. Expand
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