Social network mining of requester communities in crowdsourcing markets
Bibliographic Data
| ID | 4697962 |
|---|---|
| Authors | Daniel Schall (0000-0002-1038-0241, Siemens (Germany), corresponding author), Florian Skopik (0000-0002-1922-7892, Austrian Institute of Technology) |
| Year | 2012 |
| Volume | 2 |
| Issue | 4 |
| Pages | 329-344 |
| Publication date | 2012-12-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Network Analysis and Mining (JOURNAL) |
| Journal identifiers | ISSN: 1869-5450 • E-ISSN: 1869-5469 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s13278-012-0080-x |
| OpenAlex | W2050054881 |
| Language | EN |
| Citations received | 2 |
| References cited | 40 |
Business · Crowdsourcing · Data mining · Data science · Social media · Social network analysis · World Wide Web · Computer Science · Mobile Crowdsensing and Crowdsourcing · Spam and Phishing Detection · Web Data Mining and Analysis
Structural Holes
Maps of random walks on complex networks reveal community structure
Authoritative sources in a hyperlinked environment
Evaluating collaborative filtering recommender systems
Term-weighting approaches in automatic text retrieval
Analyzing the Amazon Mechanical Turk marketplace
Emergence of Scaling in Random Networks
"Coase's Penguin, or, Linux and "The Nature of the Firm
Identification of leaders, lurkers, associates and spammers in a social network
Identifying high betweenness centrality nodes in large social networks
Using dynamic community detection to identify trends in user-generated content
Context-sensitive detection of local community structure
Analysis of user keyword similarity in online social networks
| Citations per year | 0.17 |
|---|---|
| Citation span | 2014 - 2014 (1) |
| Highly cited | No |