Trust issues and Excel: how to open other people’s NodeXL documents

15MarMay 7, 2015 By Marc Smith

How to open a NodeXL Workbook created on a different machine

Microsoft Office applications have trust issues.

When you download a NodeXL workbook from a different machine (perhaps from http://nodexlgraphgallery.org) you may get an error like this one that mentions “trusted locations”.

************** Exception Text **************

Microsoft.VisualStudio.Tools.Applications.Runtime.

CannotCreateCustomizationDomainException:

This document contains custom code that cannot be

loaded because the location is not in your trusted

locations list: Sample_Facebook_Egonetwork.xlsx. If you

trust this document you can save and open it from a

location on your computer.

For more information,

see http://go.microsoft.com/fwlink/?LinkId=99104.

******************************************

This problem is caused by a lack of trust. Excel documents may contain harmful code (“malware”) and the solution Microsoft created was the idea of “Trusted Locations”. Only folders that have been identified as “trusted locations” will allow you to open Excel files that run embedded code, which are needed by NodeXL to run.

Below are the steps needed to make a folder a trusted location. Once you have done that, NodeXL files stored in that folder will no longer display this error when they are opened.

Step 1: Open Excel Options from the File Menu in Excel

Select: Excel File Menu>Options

The Excel Options dialog. Select “Trust Center”.

Step 2: Choose the Trust Center tab on the menu on the left

The Excel Trust Center dialog. Select “Trust Center Settings”.

Step 3: Add a new trusted location where you will store your NodeXL files

Step 4. The Excel Trusted Locations dialog. Select “Add new location…”.

The Excel Trusted Location dialog. Enter the path to your NodeXL directory here.

Select the “Subfolders of this location are also trusted”. Select OK to every dialog.

It is not recommended that the download directory for your browser be granted Trusted location status. This will require NodeXL users to download files and then copy or move them to a Trusted Location in order to open and use the complete NodeXL functionality in the file.

October 2-3, 2014: Digital Strategies for Development Summit, Asian Institute of Management, Makati City, Philippines – Mapping social media networks

22SepMay 7, 2015 By Marc Smith

I attended and participated in the October 2-3, 2014 Digital Strategies for Development Summit hosted by the Asian Institute of Management and held in Makati City, Philippines.

The event gathered 50 speakers from around the world and more than 300 participants to focus on the role of digital and social technologies for civic needs. The summit focused on bringing people from many communities into a discussion of how technology can be used for:

“…enabling a better society and an empowered community? How can various stakeholders, including Government, Private Sector and Civil Society gain more momentum for their core mandates by leveraging the use of digital technology enabled solutions? Can Digital Technology create a platform for better collaboration and cooperation amongst various stakeholders?”

I spoke about the role social network analysis can play in understanding the emerging world of social media and computer mediated collective action.

NodeXL Office Hours: Thursday 10-12 Pacific Time in Google Hangout

13JunMay 7, 2015 By Marc Smith

Hello! Each Thursday at 10AM to noon (Pacific Time), I will be taking questions and providing support to NodeXL users in a Google Hangout. Join me for a Q&A about NodeXL, SNA, Social Media, Networks, Mapping, Visualization and Analytics.

How to create a random network in NodeXL

03MarMay 7, 2015 By Marc Smith

It can be useful to create networks randomly to use as training data sets. A simple way to create a random network is to use the Excel RAND() function. To create a random network of ten nodes use the following formula in a ten by two array:

=INT(RAND()*10)

the “INT” part removes the decimal places, leaving an “Integer” whole number value.

Then copy the grid of Random Value 1 and Random Value 2 to the Vertex1 and Vertex 2 columns (starting in A3) (use Paste Values to just get the current values of the random number generator!). You can control the number of edges by copying the formula to as many rows as you want. You can control the number of nodes by changing the value the random result is multiplied by. The current formula multiplies by ten, creating up to 10 vertex values (after being reduced to an integer). Increase this value to 100 for that many different nodes. You could get much more sophisticated, creating weighted probabilities for each vertex to appear, but this is a first, simple way to “just get a network data set” fast.

When you show the graph, you may get a network visualization that looks somewhat like this:

NodeXL describes the networks you create: Graph Summary in v.203

09MarMay 7, 2015 By Marc Smith

Here is a map of connections among people who recently tweeted the term “peoplebrowsr”.

“But what does that picture mean?”

I hear this reaction frequently when I show people maps I have made of social media connections.

I often point out that the map and the data can reveal people who occupy important locations in the network as well as emergent clusters and groups.

“So why didn’t you just say so?”

I hear this reaction frequently when I explain what is important about a network.

In NodeXL version 203 we have released a new feature called Graph Summary. Our goal is to “just say so”.

In this version we introduce the basics of automatic captioning. In the NodeXL>Graph menu we now have a “Summary” button:

NodeXL will collect information about the creation and configuration of the network. The dialog box looks like this:

Note that NodeXL>Data>Save Import Details in Graph Summary must be selected in the Import menu for the “Data Import” field to be populated.

Selecting “Copy to Clipboard” will load a copy of these text fields into the buffer. An example of that caption is here:

The graph represents a network of up to 1000 Twitter
users whose recent tweets contained "peoplebrowsr". 

The network was obtained on
Friday, 09 March 2012 at 01:21 UTC. 

There is an edge for each follows relationship. 
There is an edge for each "replies-to" relationship
in a tweet. 

There is an edge for each "mentions"
relationship in a tweet. 

There is a self-loop edge for each tweet that is
not a "replies-to" or "mentions". 

The earliest tweet in the network was tweeted on
Friday, 02 March 2012 at 02:39 UTC. 

The latest tweet in the network was tweeted on
Friday, 09 March 2012 at 00:47 UTC.

The graph is directed.

The graph was laid out using the
Harel-Koren Fast Multiscale layout algorithm.

The edge colors are based on relationship values. 
The vertex sizes are based on followers values.

Overall Graph Metrics:
Vertices: 74
Unique Edges: 172
Edges With Duplicates: 123
Total Edges: 295
Self-Loops: 42
Connected Components: 15
Single-Vertex Connected Components: 13
Maximum Vertices in a Connected Component: 58
Maximum Edges in a Connected Component: 276
Maximum Geodesic Distance (Diameter): 4
Average Geodesic Distance: 2.014176
Graph Density: 0.036653091447612
Modularity: 0.288302

Top 10 Vertices, Ranked by Betweenness Centrality:
@peoplebrowsr
@andrewgrill
@traviswallis
@thenickfrost
@jas
@alexbudge
@getmingly
@milener
@jeffreyhayzlett
@johnnosta

The graph's vertices were grouped by cluster using the
Clauset-Newman-Moore cluster algorithm.

More NodeXL network visualizations are here:
www.flickr.com/photos/marc_smith/sets/72157622437066929/
and here:
www.nodexlgraphgallery.org/Pages/Default.aspx

A gallery of NodeXL network data sets is available here:
nodexlgraphgallery.org/Pages/Default.aspx?search=twitter

NodeXL is free and open and available from www.codeplex.com/nodexl

NodeXL is developed by the Social Media Research Foundation
(www.smrfoundation.org) - which is dedicated to
open tools, open data, and open scholarship.

Donations to support NodeXL are welcome through PayPal:
https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=J5AERGAAN552S

The book, Analyzing social media networks with NodeXL:
Insights from a connected world, is available from Morgan Kaufmann and from Amazon.
http://www.amazon.com/gp/product/0123822297?ie=utf8&tag=conneactio-20&linkcode=as2&camp=1789&creative=390957&creativeasin=0123822297

This caption will expand in our next several releases to include information about the top URLs, hashtags, and @usernames in text fields associated with nodes and edges. Following that we will release a series of features to allow for the extraction of keyword pairs in those text fields (our current version of this feature is described here: Keyword Networks: create word association networks from text with NodeXL (with a macro)).

October 19-20, 2011: NYC – Predictive Analytics World: Network Maps for End Users: Collect, Analyze, Visualize and Communicate Network Insights with Zero Coding

17OctMay 7, 2015 By Marc Smith

I presented on social media network analysis on October 20, 2011 in New York City at Predictive Analytics World.

A map of the connections among the people tweeting about the #Pawcon hashtag is below.

Network Maps for End Users: Collect, Analyze, Visualize and Communicate Network Insights with Zero Coding

Abstract: Networks are everywhere except the end user desktop. NodeXL, the free and open network overview, discovery and exploration add-in for the popular and familiar Excel (2007/2010) spreadsheet allows users who are comfortable making pie charts to now make useful network visualizations. Developed and released by the Social Media Research Foundation, NodeXL uses Excel as a framework, providing a GUI network browser (a “web browser”?) that novices can use quickly and experts can use to generate sophisticated results. Data importers provide access to a range of social media network data sources like Twitter, flickr, YouTube, Facebook, email, the WWW, and more through standard file formats (CSV, GraphML, Matrix). Simple to use tools can automatically analyze, visualize and highlight insights in complex network graphs. Using NodeXL, researchers have been collecting a wide range of network data sets from various social media services. These images reveal a range of common social formations in social media and point to people who occupy strategic locations in these graphs.

This is a map of the connections among the people who tweeted the term “PAWCON” on the first day of the event:

[flickr id=”6261006732″ thumbnail=”medium” overlay=”true” size=”large” group=”” align=”none”]

These are the connections among the Twitter users who recently tweeted the word #pawcon when queried on October 19, 2011, scaled by numbers of followers (with outliers thresholded). Connections created when users reply, mention or follow one another.

A larger version of the image is here: www.flickr.com/photos/marc_smith/6261006732/sizes/l/in/ph…

Top most between users:
@tapan_patel
@pawcon
@sasanalytics
@deloitteba
@kristinevick
@jamet123
@zementis
@kdnuggets
@tibcospotfire
@saspublishing

Graph Metric: Value
Graph Type: Directed
Vertices: 41
Unique Edges: 233
Edges With Duplicates: 120
Total Edges: 353
Self-Loops: 44
Connected Components: 2
Single-Vertex Connected Components: 1
Maximum Vertices in a Connected Component: 40
Maximum Edges in a Connected Component: 352
Maximum Geodesic Distance (Diameter): 4
Average Geodesic Distance: 1.87133
Graph Density: 0.15304878
NodeXL Version: 1.0.1.179

Here is an example map of the connections among the people who tweeted the term “pawcon” in Twitter on September 14th, a week prior to the event.

[flickr id=”6274836259″ thumbnail=”small” overlay=”true” size=”large” group=”” align=”none”] [flickr id=”6274836151″ thumbnail=”small” overlay=”true” size=”large” group=”” align=”none”]

Manu Sharma, Principle Research Scientist at LinkedIn gave a great presentation on the patterns found in their data. Big data, for example, showed that most of the people who previously worked at recently failed banks and financial institutions have updated their profiles to show that they mostly have new jobs at some of the remaining companies in the industry.

The event was held at the New York Hilton: Maps & Directions

NodeXL Graph Gallery on the web: Collectively Authored Archives of Networks

07SepMay 7, 2015 By Marc Smith

The NodeXL team from the Social Media Research Foundation has released a web application that allows users to upload network files and download files other users have uploaded.

The Social Media Research Foundation is dedicated to Open Tools, Open Data, and Open Scholarship.

The NodeXL Graph Gallery on the Web enables the research community to collectively gather and share data sets.

Users of NodeXL will notice a new NodeXL>Data>Export>To Web Gallery menu option which opens this dialog box:

Users will be able to browse the NodeXL Web Gallery for graphs that were recently uploaded:

Users will be able to search for graphs that contain certain keywords:

Users can then get details about the network graph and download those files they would like to investigate.

9 August 2011 – Social Media SNA Workshop – Association for Education in Journalism and Mass Communication (http://www.aejmc.com/)

31JulMay 7, 2015 By Marc Smith

Here is a map of the connections among the people who tweeted the term “AEJMC” on August 7, 2011:

The top most between people in this network are:@aejmc, @jlab, @karenrussell, @terryflynn, @natcomm, @tmccorkindale, @derigansilver, @tkell, @aejmconlineads, and @jeremyhl:

I will present a Workshop on Social Media Network Analysis and NodeXL at the 9 August 2011 – Association for Education in Journalism and Mass Communication (http://www.aejmc.com) in St. Louis, Missouri along with my colleague Professor Hernando Rojas, from the School of Journalism & Mass Communication, University of Wisconsin – Madison.

See: http://www.aejmc.com/home/events/annual-convention/

The Association for Education in Journalism and Mass Communication (AEJMC) is a nonprofit, educational association of journalism and mass communication educators, students and media professionals. The Association’s mission is to promote the highest possible standards for journalism and mass communication education, to cultivate the widest possible range of communication research, to encourage the implementation of a multi-cultural society in the classroom and curriculum, and to defend and maintain freedom of communication in an effort to achieve better professional practice and a better informed public.

Our session is:

Using NodeXL for Social Network Analysis
Tuesday — 2 pm to 5 pm
Presented by Communication Theory and Methodology Division
This pre-conference workshop examines social network analysis. Social network analysis can be used to examine message boards, blogs, and friend networks (amongmany other phenomena). Participants will learn to use the NodeXL program to conduct a network analysis. For information, contact Michel M. Haigh, Pennsylvania State University at mmh25@psu.edu.

A legend in your own network graph: NodeXL legend describes data elements

12JunMay 7, 2015 By Marc Smith

Every network visualization should have a legend that explains what the colors, edge widths, and filters are that define the network graph.

NodeXL automatically generates a network legend and displays it when the Graph Elements menu is opened:

And the “Legend” option is selected.

This will place a legend at the bottom of the visualization canvas:

A Sample Settings File for NodeXL: An automated recipie for making Twitter network visualizations

12JunMay 7, 2015 By Marc Smith

Starting in version .165 of NodeXL we have supported the idea of an options file that can be imported, exported and exchanged among users.

If you have set all the knobs and dials of your copy of NodeXL just right, you can export these adjustments and configurations into a single file. Use the NodeXL>Options>Export feature to create a named file containing your settings. You can now exchange this file with others. If you receive an options file, you can use the NodeXL>Options>Import feature to pick it out from the file system and set your copy of NodeXL to the settings defined in that file.

If you use the related NodeXL>Options>Use Current for New feature you can set the defaults for NodeXL to the settings contained in any imported options file.

I have been fine tuning a settings file that generates network visualizations that are tailored for the Twitter networks I have been making many of. I have saved these sample settings file for NodeXL and you can try them yourself here: NodeXL-Twitter Network-Options Settings.NodeXLOptions.

Download this file, rename it by removing the .txt extension and load it into your copy of NodeXL.

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