This is the attentive betweenness centrality algorithm, which infers importance scores of actors in social networks. Currently, it takes undirected and unweighted graph. However, each input edge must have weight which could be any number now. It is possible to modify the source code to get rid of this limitation. We keep this for future expansion to weighted graph. Copyright: ========== You can modify and redistribute the program. Please DO NOT remove copyright and authors information in the source code. For more copyright information, please refer to attached gpl.txt. How to compile: =============== The code use boost library, so, we suppose you already have boost library installed on your system. For more information about boost library, please visit: http://www.boost.org/. The program was written in C++ using the Netbeans 6.9 IDE (http://www.netbeans.org) on an Opensuse 11.4 64-bit computer. You should get a compressed netbeans project folder. Extract the compressed folder to a convenient place, and get into 'AttnCentrality' folder. Type 'make' command in a terminal within the folder. After these steps, you should get an executable 'attncentrality'. There is a symbol link to the executable in the folder for quick access to the program. The program was successfully compiled and ran on OpenSuse 11.4, Ubuntu 10.4, and Mac OS X 10.5.x. How to run: =========== In a terminal, type the executable name, following by a graph and optional alpha. For example: attncentrality graph.txt 0.5 The program reads 'graph.txt' and runs the ABC centrality with alpha = 0.5. The results will be stored in a text file named 'results.txt'. Each line of the results is a pair of node name and score, tab delimited. Graph format: ============= Currently, ABC only takes undirected, unweighted graph. The graph file must be in format of: Questions: ========== Any concerns, please send a message to lux3@cs.rpi.edu.