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20112013
most citedOverlapping Community Detection in Networks: the State of the Art and Comparative Study

937 citations · 1.8k across the 11 of their papers we have counts for

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Showing 2011Show all

8 papers · 1 filter

physics.soc-ph2011★ 78 cited

Evolution of opinions on social networks in the presence of competing committed groups

J. Xie, J. Emenheiser, M. Kirby +3

Public opinion is often affected by the presence of committed groups of individuals dedicated to competing points of view. Using a model of pairwise social influence, we study how…

cs.SI2011★ 937 cited

Overlapping Community Detection in Networks: the State of the Art and Comparative Study

Jierui Xie, Stephen Kelley, Boleslaw K. Szymanski

This paper reviews the state of the art in overlapping community detection algorithms, quality measures, and benchmarks. A thorough comparison of different algorithms (a total of f…

cs.SI2011★ 86 cited

SLPA: Uncovering Overlapping Communities in Social Networks via A Speaker-listener Interaction Dynamic Process

Jierui Xie, Boleslaw K. Szymanski, Xiaoming Liu

Overlap is one of the characteristics of social networks, in which a person may belong to more than one social group. For this reason, discovering overlapping structures is necessa…

cs.NE2011

Using Hopfield to Solve Resource-Leveling Problem

Caixing Liu, Jierui Xie, Yueming Hu

Although the traditional permute matrix coming along with Hopfield is able to describe many common problems, it seems to have limitation in solving more complicated problem with mo…

cs.MM2011★ 4 cited

Scale-Invariant Local Descriptor for Event Recognition in 1D Sensor Signals

Jierui Xie, Mandis S. Beigi

In this paper, we introduce a shape-based, time-scale invariant feature descriptor for 1-D sensor signals. The time-scale invariance of the feature allows us to use feature from on…

cs.SI2011★ 165 cited

Community Detection Using A Neighborhood Strength Driven Label Propagation Algorithm

Jierui Xie, Boleslaw K. Szymanski

Studies of community structure and evolution in large social networks require a fast and accurate algorithm for community detection. As the size of analyzed communities grows, comp…