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Facebook Likes Dataset

 
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MessagePosté le: Jeu 11 Jan - 03:08 (2018)    Sujet du message: Facebook Likes Dataset Répondre en citant




Facebook Likes Dataset
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Newman, M. Weighted static one-mode network: tnet-format; UCINET-format In the third network, the ties among the researchers are differentiated in terms of advice (Please indicate the extent to which the people listed below provide you with information you use to accomplish your work). Best Regards, Xiaoge Zhang Reply 27. You can use the symmetrise-function to do this. From you description, you might want to keep this temporal aspect in your analysis. Reply 2. is it true that, if there is 1 3 32 , I add 3 1 32 to the matrix and for this row ( 3 1 35 ) in the tnet-format , I sum 32 and 35 and consider (32+35) as tie weight between node 1 and 3? Reply 37. Note: Please do cite the mentioned reference if you use a dataset. De Meo, E. This dataset was used in Colizza et al. Dataset statistics Nodes 4039 Edges 88234 Nodes in largest WCC 4039 (1.000) Edges in largest WCC 88234 (1.000) Nodes in largest SCC 4039 (1.000) Edges in largest SCC 88234 (1.000) Average clustering coefficient 0.6055 Number of triangles 1612010 Fraction of closed triangles 0.2647 Diameter (longest shortest path) 8 90-percentile effective diameter 4.7 . Please cite those which are relevant to your research if you use any Facebook dataset. The forum represents an interesting two-mode network among 899 users and 522 topics in that a weight can be assigned to the ties based on the number of messages or characters that a user posted to a topic. Best, Tore # Load tnet and dataset library(tnet) data(tnet) # Directed net netDirected <- OnlineSocialNetwork.n1899.net netDirected[netDirected[,"i"] %in% c(1,3) & netDirected[,"j"] %in% c(1,3),] # Undirected network netUndirected <- symmetrisew(netDirected, method="SUM") netUndirected[netUndirected[,"i"] %in% c(1,3) & netUndirected[,"j"] %in% c(1,3),] Reply 38. Rasheed November 23, 2009 at 8:15 am I just downloaded your Online Social Network dataset in UCINET format. This dataset contains some nodal attributes. Thanks again. Useful links: PDF CACM S. Note that the identification numbers do not match with the online social network. Is there any tool which provides conversion from edge list format to node list format? Kindly let me know. Navneet Aggarwal June 13, 2009 at 5:13 am Hi Tore, First off, congratulation on the completion of your Ph.D. Even thought this type of networks is directed by nature as a flight is scheduled from one airport and to another, the networks are highly symmetric (Barrat et al., 2004). For example: 1 2 3 1 would be the two ties from node 1 to node 2 and from node 3 to node 1. The two-mode networks are projected onto one-mode networks using the procedure outlined on the projecting two-mode networks onto weighted one-mode networks-page. Muad October 24, 2013 at 6:24 pm Hi Dr Tore, As you mentioned above, the dataset C.elegans Neural Network contains 14 duplicated ties and that you merged each duplicate tie into one tie by summing their weights. Crawling Facebook for social network analysis purposes. Do send me an email if you do you an issue. When you contact me for data requests, please provide information about your academic status (your home institution, your current position) and explain in brief how you will use the data. University of Chicago Press, Chicago, IL. roya May 29, 2013 at 10:51 pm Dear tore, thanks for sharing the data sets with us. These networks was used by Cross and Parker (2004). The one you compiled from Newman how did you actually do that? I could only find a compiled, weighted, one-mode version from him. This dataset was the main dataset used in my Ph.D. Especially interesting was that many of the entrepreneurs mentioned the same individuals who were connectors in their initial international ventures. Hend Kareem January 12, 2015 at 6:32 pm Hi, I wonder can one get information about who is friend with whom for the first data set, Facebook-like social network? BR. its really nice and thanks for the effort. Tore Reply 32 5a02188284
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