I will speak about the value of a network perspective for the discovery of fraud and corruption in financial data at the December 9th session of the World Bank’s upcoming meeting of the Stolen Asset Recovery Initiative.
“The World Bank Group’s International Corruption Hunters Alliance (ICHA) brings together heads and senior officials of corruption investigating bodies and prosecuting authorities, anti-corruption experts, academics, and representatives of international organizations from over 130 countries. The 2014 meeting of the Alliance will focus on fighting corruption – and the vast illicit outflows generated by corruption – by sharing know-how and experiences in the use of both traditional and alternative corruption fighting approaches.”
All financial transactions create a network as one person transfers money from one account to another. A list of transactions creates a web of connections with an emergent shape or pattern. Within these patterns are key positions occupied by people with special power in the network. Mapping these transaction networks can reveal the hidden traces of financial crime.
Imported Twitter networks now have an “in-reply-to tweet ID” column. This is a useful data element for building “paths” that capture how information flows through a network.
When you lay out each of the graph’s groups in its own box, you can now select how the boxes are laid out. Go to NodeXL>Graph>Layout>Layout Options in the Excel ribbon. (Thanks to Cody Dunne for this feature.)
The Check for Updates item has been removed from the Excel ribbon. NodeXL now automatically checks for updates once a day. Once this release is installed, NodeXL will automatically update itself when a new release is available. You will no longer have to manually download and install new releases. This release and those that follow will all be referred to as “NodeXL Excel Template 2014.” New releases will continue to have version numbers, but the numbers will be less important in light of the new auto-update feature.
If you use third-party graph data importers, such as the Social Network Importer for NodeXL, note that the folder where the importers are stored must be specified in the NodeXL>Data>Import>Import Options dialog:
If you use the NodeXL Network Server, an advanced command-line program that downloads a network from Twitter and stores the network on disk in several file formats, note that the program is no longer a part of NodeXL Excel Template. See “Using the NodeXL Network Server command-line program with NodeXL Excel Template 2014” at http://nodexl.codeplex.com/discussions/522830.
When a Twitter network is imported, the hashtags in the “Hashtags in Tweet” (or “Hashtags in Latest Tweet”) column are now all in lower case. Previously, identical strings with different case letters would be counted differently. This is no longer the case and the result is that terms that had been divided are now unified. These terms will now have higher values and there will be more diversity in the top ten list.
Thanks for using NodeXL and stay tuned for additional updates!
The talk will focus on free and open tools for creating network maps and reports that can illuminate the landscape of social media.
The graph represents a network of 633 Twitter users whose tweets in the requested date range contained “sqlpass”, or who were replied to or mentioned in those tweets. The tweets in the network were tweeted over the 15-day, 2-hour, 48-minute period from Tuesday, 25 February 2014 at 00:26 UTC to Wednesday, 12 March 2014 at 03:15 UTC.
There is an edge for each “replies-to” relationship in a tweet, an edge for each “mentions” relationship in a tweet, and a self-loop edge for each tweet that is not a “replies-to” or “mentions”.
The graph’s vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm. The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.
The edge colors are based on edge weight values. The edge widths are based on edge weight values. The edge opacities are based on edge weight values. The vertex sizes are based on followers values. The vertex opacities are based on followers values.
Top 10 Vertices, Ranked by Betweenness Centrality:
Networks are everywhere but collecting, analyzing, visualizing, and gaining insights into connected structures can require advanced technical skills. This session presents a free, easy-to-use tool for network analysis that builds on the familiar Excel spreadsheet called NodeXL. If you can make a pie chart, you can get insights into networks. The tool makes it easy to collect data from a range of social media (Twitter, Facebook, YouTube, etc.). Quickly create visualizations and reports on the shape of connected groups. Identify the key people, groups and topics in a community. Network analysis can reveal the hidden structures in streams of interactions.
Mapping Twitter Topic Networks:
From Polarized Crowds to Community Clusters
The paper documents the distinct patterns of connection that emerge when people talk to one another using social media services like Twitter. The paper includes six network visualizations that clearly demonstrate the diverse ways people connect to people when using online tools.
Ballroom ABNetworks are everywhere, particularly in social media. Understanding networks can quickly reveal the key people, groups, and topics that matter most. But the tools to collect, analyze, visualize, and gain insights into connected structures have remained complex. Now the free and open NodeXL application makes network analysis tasks as easy as making a pie chart. The Network Overview Discovery and Exploration add-in for Excel (2007, 2010, 2013) extends the familiar spreadsheet, enabling users to easily access networks from a range of data sources including Facebook, YouTube, Twitter, Flickr, email, message boards, Wikis, blogs, and other repositories of connections. With simple automation tools, NodeXL users can calculate a range of network metrics, create a visualization, and generate a report highlighting key people, groups, and top URLs, hashtags, words and word pairs used in the discussion network. Network maps have revealed many of the hidden structures of social media, defining the major differences in the shapes and structures created as people link to one another.
If you have questions on social network analysis, meet with Marc to talk about:
NodeXL and related network analysis and visualization tools
How to collect, store, analyze, visualize, summarize and publish social network reports with just a few clicks (and no coding)
How to identify key influential people and subgroups within a conversation network
How to apply social network analysis to social media marketing
How to apply organizational network analysis to enterprise collaboration
Above is a map of the connections among the people who recently tweeted the term “strataconf” over the 7-day, 19-hour, 38-minute period from Sunday, 26 January 2014 at 21:53 UTC to Monday, 03 February 2014 at 17:32 UTC. The key people in the network at this point are:
You can make these types of maps with just a few clicks using NodeXL.