Social Network Analysis of Online Marketplaces

Kumar, Pushpa; Zhang, Kang

doi:10.1109/icebe.2007.4402116

Cited by 9 publications

(6 citation statements)

References 8 publications

(12 reference statements)

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“…• eBay buyer/seller relationships obtained from eBay [19], where user-name string length 'S' is chosen from the following two cases: i) S = 3 ii) S = 10.…”

Section: Implementation/experimental Resultsmentioning

confidence: 99%

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From Tree to Graph - Experiments with E-Spring Algorithm

Kumar¹,

Zhang²,

Huang

2009

Visual Information Communication

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Abstract. Graph drawing and visualization represent structural information as diagrams of abstract graphs and networks. E-Spring Algorithm, derived from the popular spring embedder model, was proposed to eliminate node overlaps in the drawings of clustered directed acyclic graphs Gc. In this paper, we apply the E-Spring algorithm to general graphs by minimizing edge-node intersections. Initially, a tree structure is extracted from the original graph using the breadth-first search (BFS) algorithm. The extracted tree is then visualized without node overlaps using the E-Spring algorithm, and the remaining non-tree edges are appended to this visualization. A post-processing step that implements edge routing is performed on the obtained visualization to eliminate residual edge-node intersections. This method has been validated by visualizing eBay buyer-seller relationships and Graph Catalog benchmarking data.

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“…• eBay buyer/seller relationships obtained from eBay [19], where user-name string length 'S' is chosen from the following two cases: i) S = 3 ii) S = 10.…”

Section: Implementation/experimental Resultsmentioning

confidence: 99%

“…We plotted the social network graph G(V, E) extracted from eBay [19]. eBay customer data for various buyers and sellers was mined from its production environment using the Web services API.…”

Section: Ebay Datamentioning

confidence: 99%

From Tree to Graph - Experiments with E-Spring Algorithm

Kumar¹,

Zhang²,

Huang

2009

Visual Information Communication

Self Cite

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“…The input data for this implementation is eBay buyer/seller relationships obtained from eBay [15], where user-name string length 'S' is chosen from one of the following three cases: i) S = 3 ii) S = 10, and iii) S = non-uniform (3 ≤ S ≤ 10). Figure 3a shows the screenshot for S = 30 oval child leaf nodes, Figure 3b represents rectangular child leaf nodes for S = 10, and Figure 3c depicts screenshot for oval child leaf nodes with S = non-uniform label length (3 ≤ S ≤ 10).…”

Section: Resultsmentioning

confidence: 99%

“…The resultant graphs obtained satisfy various aesthetic criteria like overall symmetry and readability. Experimental analysis and visualization of this method for eBay buyer-seller relationships [15] are reported, and show overall DAG area reductions in the range of 45% to 79%. The rest of this paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

Visualization of clustered directed acyclic graphs with node interleaving

Kumar

Zhang

2009

Proceedings of the 2009 ACM Symposium on Applied Computing

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Graph drawing and visualization represent structural information as diagrams of abstract graphs and networks. An important subset of graphs is directed acyclic graphs (DAGs). E-Spring algorithm, extended from the popular spring embedder model, eliminates node overlaps in clustered DAGs by modeling nodes as charged particles whose repulsion is controlled by edges modeled as springs. The drawing process needs to reach a stable state when the average distances of separation between nodes are near optimal. This paper presents an enhancement to E-Spring to introduce a stopping condition, which reduces equilibrium distances between nodes and therefore results in a significantly reduced area for DAG visualization. It imposes an upper bound on the repulsive forces between nodes based on graph geometry. The algorithm employs node interleaving to eliminate any residual node overlaps. These new techniques have been validated by visualizing eBay buyer-seller relationships and resulted in overall area reductions in the range of 45% to 79%.

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“…Regarding SNA in online marketing and exchanging platforms, Kumar and Zhang use SNA to study online customer interaction behaviors in eBay [6]. Swamynathan et al study the correlation between social networks and user transaction satisfaction in OverStock Auction, a large-scale online auction platform [13].…”

Section: Related Research and Motivationmentioning

confidence: 99%

Understanding user behavior in a local social media platform by social network analysis

Tang

Hämäläinen

Virolainen³

et al. 2011

Proceedings of the 15th International Academic MindTrek Conference: Envisioning Future Media Environments

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Characterizing user behavior by social network analysis in social media has been an active research domain for a long time. However, much previous research has focused on the large-scale global social media such as Facebook, Wikipedia and Twitter. Comparatively, little research has been done for the local social media. In this paper, We study the user behavior by social network analysis in a campus-based social media platform for exchanging goods and services. We also study the correlation between social networks and users' exchanging behaviors. Finally, we discuss the implications of our findings and future work.

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Social Network Analysis of Online Marketplaces

Abstract: Abstract

Cited by 9 publications

References 8 publications

From Tree to Graph - Experiments with E-Spring Algorithm

From Tree to Graph - Experiments with E-Spring Algorithm

Visualization of clustered directed acyclic graphs with node interleaving

Understanding user behavior in a local social media platform by social network analysis

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