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Group-in-a-box – a new layout option in NodeXL (v.164)

17MarMay 7, 2015 By Marc Smith

Attractive and well designed network visualization layouts are complex to automate.  Many researchers have devoted a great deal of effort to refining algorithms that assign the best set of positions to a set of nodes.  In many cases a layout algorithm will work well for some types of graphs and not others.  NodeXL has a few network visualization layout algorithms to choose from (Harel-Koren and Fruchterman-Reingold) and we plan to add one or two more in the coming months based on leading new approaches to automated layout.

Today, we release a new NodeXL feature in version  .164  that we think will improve the results generated by other layout algorithms: Group Layout.  In the Layout Options menu in the NodeXL Network Graph Pane (called “Document Actions” by Excel) you will find that the dialog box has been updated:

Selecting the new “Lay out each of the graph’s groups in its own box and sort the boxes by group size” option and checking the “Show each box’s outline” can generate an image that neatly places each group in a bounded region.

20110313-NodeXL-Twitter-msrtf11 OR techfest group layout

Here we see the set of connections among the people who tweeted the string “msrtf11 OR techfest” – referring to the Microsoft Research TechFest 2011 event that took place in early March in Redmond, Washington.  This map clarifies the set of set of relationships among sub-groups within the graph.

Contrast this with the layout created without this feature turned on:

We still have some refinements coming that will improve this layout further (for example, the neat grid of isolated nodes takes an extra step today, we will try to make that happen automatically soon) but this is a nice step in making network graphs easier to understand.  Let us know what you think!

Posted in All posts, Companies, Connected Action, Foundation, Network visualization layouts, NodeXL, SMRF, Social Network Analysis, Sociology, Twitter, University, Visualization Tagged 2011, Chart, group, Group Layout, Layout, Map, March, network, NodeXL, SMRF, SMRFoundation, SNA, Social Media Research Foundation, Treemap, v164, Visualization 6 Comments

How to build a collection of influential followers in Twitter using social network analysis and NodeXL

05MarMay 7, 2015 By Marc Smith

Here is a recipe for finding and building collections of influential Twitter users relevant to your goal and message.

A common question related to social media that I am often asked is: “how do we grow our twitter followers?”  I try to re-frame that question as “how can we get our message viewed by the right people?” and its related question: “who could best pass our message along?”

The goal is not to gain many followers, but rather to gain well positioned followers!  A well positioned follower is someone who talks about topics related to your topic and is located at the center of many relationships with other people in that topic network.  These highly central people are able to get their message to be visible to many people. If they re-tweet you, your message will go far.  Why would they re-tweet you?  First, they have to be able to hear you to re-tweet you and that means that you need to get these people to follow you.  Second, you need to say something sensible enough to be worth re-tweeting.

The task is finding the important users to focus on.  To find them, create a network map of the relevant topics.  A few people in these network maps will occupy key positions in which they have many connections or have special ties that bridge gaps between sub-groups.  There are often only a few of these people in any topic area.

20110121-NodeXL-Twitter-stateoftheunion high between users

Find these strategically located people and follow them and often they will follow you back. A good proxy for the strategic value of a person’s location is their “betweenness centrality” – a measure of how much a person acts a bridge between others.

20110121-NodeXL-Twitter-stateoftheunion top between users list

If the people you select and follow do not immediately follow you back there is another opportunity to get them to follow you.  If you re-tweet particularly good content from the people you have selected to follow there is a good chance that you will be followed back.

Once you have identified, followed, and been followed back by some fraction of the influential people around your topics of interest you have a increased chance that your tweets will be re-tweeted.  For each re-tweet, your message is exposed to a potentially large and highly targeted group of people.  Over time it is possible to create a relationship with a collection of highly influential participants who may be interested in sharing your message with their followers.

Posted in All posts, Companies, Connected Action, Industry, Measuring social media, NodeXL, Social Interaction, Social network, Social Network Analysis, Social Roles, Twitter, Visualization Tagged 2011, Chart, Followers, graph, Map, network, NodeXL, SMRF, SMRFoundation, SNA, Social Media Research Foundation, Strategy, Twitter 1 Comment

11 March 2011: San Francisco – Future of Networks event

05MarMay 7, 2015 By Marc Smith

On 11 March 2011, I will be speaking at:

Organizational and Social Media Network Analysis:
Next Practices in Organizational Networks, Analytics and Media

Along with Valdis Krebs, Chief Scientist, http://thenetworkthinkers.com/


Valdis will be speaking about Organizational Network Analysis – Introduction to Enterprise Networks, followed by a InFlow 3.1 Workshop: Social Network Analysis with InFlow 3.1

I will be speaking about Social Media Network Analysis with NodeXL.

Preservation Park
1233 Preservation Park Way
Oakland, CA 94612
(510) 874-7580
(click for map)


Tell a Friend
Add to Calendar

Posted in All posts, Collective Action, Companies, Conference, Connected Action, Foundation, Industry, Measuring social media, Metrics, NodeXL, Research, SMRF, Social Interaction, Social Media, Social Network Analysis, Sociology, Talks, Twitter, Visualization Tagged 2011, Analysis, Lecture, Marc Smith, March, Networks, NodeXL, Oakland, Presentation, SNA, Social network, Talk, Valdis, Valdis Krebs, workshop

2011 State of the Union: Mapping the connections among Twitter users who tweet about SOTU

22JanMay 7, 2015 By admin

The United States State of the Union address this year will be held Tuesday evening, 25 January 2011.

The event is a globally visible opportunity for the President of the United States to present the Administration’s vision for its agenda for the year to the people of the US and the world.

The hashtag #stateoftheunion is already very active in Twitter.

This is a NodeXL map of the connections among people who recently tweeted the string “stateoftheunion” on 21 January, 2011.
20110121-NodeXL-Twitter-stateoftheunion highlighted top between user

The most between user, @keitholbermann, is highlighted.  Two major clusters emerge, shown arbitrarily here as green and blue, and which are more clearly seen in the filtered graph below the list.

Summary network statistics:

Graph Type Directed
Vertices 1259
Unique Edges 8014
Edges With Duplicates 544
Total Edges 8558
Connected Components 306
Single-Vertex Connected Components 293
Maximum Vertices in a Connected Component 937
Maximum Edges in a Connected Component 8513
Maximum Geodesic Distance (Diameter) 9
Average Geodesic Distance 3.140191
Graph Density 0.00522786

20110121-NodeXL-Twitter-stateoftheunion top between users list

The most “between” contributors in the network are:

@keitholbermann, @borowitzreport, @thefix, @katyinindy,
@america1first, @wbconservative, @westwingreport, @dailykos,
@writer2go, and @gottalaff

When contributors with low “betweenness” are filtered out of the graph, two dominant clusters become easier to discern.  To the left are supporters of the President and to the right are those critical of the Administration.  A representative tweet from this cluster is highlighted.

20110121-NodeXL-Twitter-stateoftheunion high between users

Posted in All posts, Collective Action, Data Mining, Foundation, Measuring social media, Metrics, Network clusters and communities, NodeXL, Politics, SMRF, Social Interaction, Social Media, Social network, Social Network Analysis, Social Roles, Social Theories and concepts, Sociology, Twitter, Visualization Tagged 2011, Chart, cluster, Diagram, Map, Media, NodeXL, Poltics, SNA, Socia, socialmedia, SOTU, State, State of the Union, Twitter, Union 3 Comments

HICSS 2011 Paper: EventGraphs: Charting Collections of Conference Connections

09JanMay 7, 2015 By Marc Smith

A recent paper “EventGraphs: Charting Collections of Conference Connections” by Marc Smith from Connected Action, Professor Derek Hansen (College of Information Studies) and Professor Ben Shneiderman (Computer Science/Human Computer Interaction Lab) both from the University of Maryland and has been accepted for publication at the 2011 Hawaii International Conference on System Sciences (HICSS) Conference.  This is the 44th year for the conference. Derek Hansen presented the paper on January 7, 2011.

Hansen, D., Smith, M., Shneiderman, B., EventGraphs: charting collections of conference connections. Hawaii International Conference on System Sciences. Forty-Forth Annual Hawaii International Conference on System Sciences (HICSS). January 4-7, 2011. Kauai, Hawaii.

http://www.cs.umd.edu/localphp/hcil/tech-reports-search.php?number=2010-13

Our paper is about visualizing social media and it describes the visualization of the patterns of connections formed when people tweet about events like conferences and news stories.

EventGraphs are social media network diagrams constructed from content selected by its association with time-bounded events, such as conferences. Many conferences now communicate a common “hashtag” or keyword to identify messages related to the event. EventGraphs help make sense of the collections of connections that form when people follow, reply or mention one another and a keyword. This paper defines EventGraphs, characterizes different types, and shows how the social media network analysis add-in NodeXL supports their creation and analysis. The paper also identifies the structural and conversational patterns to look for and highlight in EventGraphs and provides design ideas for their improvement.

A collection of EventGraphs are available in flickr: http://www.flickr.com/photos/marc_smith/sets/72157625618025980/

The EventGraph for HICSS this year is here: 20110109-NodeXL-Twitter-HICSS

The top most between contributors to the HICSS Twitter graph this year are: @arcticpenguin @avantgame @barrywellman @clifflampe @dalprof @chandlerism @shakmatt @marc_smith @shen045 and @thecatandthekey

Here is the data set: 20110109-NodeXL-Twitter-HICSS
Graph Metric Value
Graph Type Directed
Vertices 92
Unique Edges 243
Edges With Duplicates 71
Total Edges 314
Self-Loops 0
Connected Components 21
Single-Vertex Connected Components 18
Maximum Vertices in a Connected Component 69
Maximum Edges in a Connected Component 307
Maximum Geodesic Distance (Diameter) 8
Average Geodesic Distance 3.081693
Graph Density 0.032967033

NodeXL Version 1.0.1.159

An article about social media visualization Social Seen: Analyzing and Visualizing Data from Social Networks by Hunter Whitney, appeared in UX Magazine on December 15, 2010.  It provides a great round up of tools and approaches to mapping populations in social media spaces.

Previous HICSS papers:

Gleave, Eric, Howard T. Welser, Marc Smith, and Thomas Lento.  2009.  “A conceptual and operational definition of social role in online community.”   In Proceedings of the 42nd  Hawaii International Conference on Systems Sciences (HICSS), January 5-8. Computer Society Press.  (Best Paper, Digital Media and Communication Mini-Track)

2009 – HICSS – 42 – Best Paper – A Conceptual and Operational Definition of ‘Social Role’ in Online Community

Fisher, D., Smith, M., and Welser, H. You Are Who You Talk To, Proceedings of HICSS, January 2006. (Best Paper, Digital Media and Communication Program)

http://www.connectedaction.net/wp-content/uploads/2009/08/2006-HICSS-You-Are-Who-You-Talk-To-Detecting-Roles-in-Usenet-Newsgroups.pdf

Viégas, Fernanda B., Marc Smith. “Newsgroup Crowds and AuthorLines: Visualizing the Activity of Individuals in Conversational Cyberspaces“, Proceedings of Hawaii International Conference on Software and Systems (HICSS) 2004. (Best Paper: Persistent Conversation Minitrack)

http://www.connectedaction.net/wp-content/uploads/2009/08/2004-HICSS-Viegas-and-Smith-Newsgroup-Crowds-and-Author-Lines.pdf

Here are some sample event graphs:
[flickrset id=”72157625618025980″ thumbnail=”square”]

Posted in All posts, Conference, Connected Action, Data Mining, Ecology, Foundation, HICSS, Maryland, Measuring social media, Network clusters and communities, Network data providers (spigots), Network metrics and measures, NodeXL, Papers, Research, SMRF, Social Interaction, Social network, Social Network Analysis, Social Theories and concepts, Twitter, University, Visualization Tagged 2011, Chart, Conference, Event, EventGraphs, graph, Hashtag, HICSS, Map, network, Paper, Publication, SMRF, SMRFoundation, SNA, Social Media Research Foundation, Twitter, Visualization

Geocode your Twitter network with NodeXL

19DecMay 7, 2015 By Marc Smith

As mobile devices become a major method for authoring and consuming social media, location data is increasingly a part of many posts, tweets, check-ins, and messages.  Many Twitter clients, for example, can add the user’s current latitude and longitude to the metadata associated with a tweet.  Other systems like Facebook Places, Google Latitude and Foursquare encourage users to declare  where they are to the world, often passing the information to other social media sites.

Using this location data in network analysis opens up a range of new opportunities.  Instead of a person – to – person social network, location data allows people to be linked to places and, by extension, places can be linked to other places based on the patterns of connection people create when located in a particular place.  A convergence of network analysis and Geographic Information Systems in underway.  A great example of this can be found in this wonderful video from the BBC which demonstrates the idea by mapping the flow of telephone calls, texts, and data around the UK and the wider world.


Link on the BBC

Even better is this video from the SensibleCity group at MIT:

Now, NodeXL (v.156) has the first of a series of features that will start to approximate the experience displayed in the video by supporting the import of location data about networks and plotting networks onto maps.

For now, we have started importing latitude and longitude data that Twitter makes available.  If you check “Add a Tweet column to the Vertices worksheet” in NodeXL, Data, Import, From Twitter Search Network or From Twitter User Network, the Twitter user’s geographical coordinates will be added to the Vertices worksheet when they are available.

Note that not every tweet has a latitude and longitude, in fact many do not (yet).  Further, note that not every latitude and longitude is accurate, many are not.

We need to implement more features for better location data support in a NodeXL workbook, but this is a start.  We are interested in exploring geospatial networks and Twitter is a great data source.  With this data in place we may look into features that emit KML files for exploration in other packages like Google Earth.  A nifty Google Earth/Spreadsheet importer can take small sets (400) of location data points in a spreadsheet and export them to a KML file, something we could implement in the future as well.  In addition we may be able to connect directly with services like Bing Maps and Google Maps to display connections between nodes with known locations.  Metrics that calculate the distance between nodes seem sensible as well.

Location coordinates are the key to a cornucopia of related data about a place.  Given a latitude and longitude it is possible to find the name of the city it is located in, look up data about that location in official records as well as resources like Wikipedia.  Income, education, property values, weather, photos, and more can be pulled together from just a simple lat/long.  All of these attributes could be used to cluster or illustrate the network visualization.

Posted in All posts, APIs and File Formats, Foundation, Location, Measuring social media, Mobile Devices, Network data providers (spigots), Network metrics and measures, Network visualization layouts, NodeXL, Sensors, SMRF, Social Media, Social network, Social Network Analysis, Technology, Twitter, Visualization Tagged 2010, API, Chart, Connection, Distance, geo, Geolocation, graph, Lat, Location, Long, Map, network, NodeXL, November, Place, SMRF, SMRFoundation, Social Media Research Foundation, Space, Spigot, Tweet, Twitter, update 1 Comment

How to schedule the creation of a network with NodeXL and Windows Task Scheduler

23AugMay 7, 2015 By Marc Smith

NodeXL has a number of data importers that can create a network of connections from social media data sources like Twitter, YouTube, flickr, email, and the WWW (along with a number of other data import formats like GraphML, UCINet, CSV, and other Excel workbooks with data).

To create a network you just select the search terms and configurations you want from the NodeXL>Data>Import menu.

If you want to create the same network every day (or at any schedule), a recent feature (since version .125) of NodeXL can help. NodeXLNetworkServer.exe is an application that ships with NodeXL along with a sample configuration file called SampleNetworkConfiguration.xml. By editing the configuration file you can set NodeXL to collect anything available in the menu through Excel.  So far we have exposed the two Twitter data collectors (more on the way) so the configuration file asks you to select a search term or a user’s name, the size of the network and the details you want reported along with the location and name of the destination file that NodeXL will create.  Answer these questions by editing the config file and save it with a useful name that includes the search term.

Step by step details after the jump:

Continue reading →

Posted in All posts, Connected Action, Measuring social media, Metrics, Network data providers (spigots), NodeXL, Social Media, Social Network Analysis, Sociology, Twitter Tagged 2010, Chart, Collector, Data, Data Collector, graph, How to, network, NodeXL, Scheduled, SMRF, SMRFoundation, SNA, Social Media Research Foundation, Task Scheduler 7 Comments

Paper: Tech Report at University of Maryland on EventGraphs

08JulMay 7, 2015 By Marc Smith

A new paper on visualizing social media has been released on the University of Maryland, Human Computer Interaction Laboratory tech report archive.  Co-authored by Derek Hansen,  myself, and Ben Shneiderman, the paper describes and visualizes the patterns of connections formed when people tweet about events like conferences and news stories.

EventGraphs_2010_HCIL_Tech_Report

http://www.cs.umd.edu/localphp/hcil/tech-reports-search.php?number=2010-13

Hansen, D., Smith, M., Shneiderman, B.
EventGraphs: Charting Collections of Conference Connections
HCIL-2010-13

EventGraphs are social media network diagrams constructed from content selected by its association with time-bounded events, such as conferences. Many conferences now communicate a common “hashtag” or keyword to identify messages related to the event. EventGraphs help make sense of the collections of connections that form when people follow, reply or mention one another and a keyword. This paper defines EventGraphs, characterizes different types, and shows how the social media network analysis add-in NodeXL supports their creation and analysis. The paper also identifies the structural and conversational patterns to look for and highlight in EventGraphs and provides design ideas for their improvement.

Posted in All posts, Community, Connected Action, Maryland, Measuring social media, NodeXL, Papers, Research, Social Interaction, Social Media, Social network, Social Network Analysis, Sociology, Twitter, University, Visualization Tagged 2010, Analysis, Chart, EventGraph, graph, HCIL, June, Maryland, network, NodeXL, Report, SMRF, SMRFoundation, SNA, social, Social Media Research Foundation, Tech, UMD, University, Visualization

Mapping the connections among people who tweet #sunbelt

03JulMay 7, 2015 By Marc Smith

The International Sunbelt Social Network Conference is the official conference of the International Network for Social Network Analysis (INSNA).

This year’s INSNA “Sunbelt” conference is at the  Riva del Garda Fierecongressi, Trento, Italy!  Here is the 2010 INSNA Sunbelt Program.

This is the NodeXL map of connections among people who tweeted the hashtag used for the conference “#sunbelt”.

2010 - July - NodeXL - sunbelt - 2010-07-01

Having now seen several of these maps for other topics and events (see: http://www.flickr.com/photos/marc_smith/sets/72157622437066929/) this map can be placed in context.  It is a small group, but has a high density of connections.  It lacks isolates, the people who say the term but do not connect to others who say that term.  This means that this is a very “in-group” population: if you know to use the #sunbelt hashtag, you probably connect to someone else who uses the term.  It is a single major cluster of connected people, no obvious sub-graphs or clusters are visible.  Not everyone is central in the graph, and those who are have a prominent role in the network science community.  Here is the top ten list of #sunbelt mentioning twitter users ranked by betweeness centrality.

miriamnotten
barrywellman
memeticbrand
isidromj
drewconway
gephi
kristtina
danevans87
valdiskrebs
ciro

Posted in All posts, Conference, INSNA Sunbelt, Measuring social media, NodeXL, Social Media, Social network, Social Network Analysis, Twitter, Visualization Tagged 2010, Chart, Conference, graph, INSNA, July, June, Map, network, NodeXL, SMRF, SMRFoundation, SNA, social, Social Media Research Foundation, Sunbelt, Twitter, Visualization

New NodeXL Network Server (v1.0.1.126) – Frequently Asked Questions

14JunMay 7, 2015 By Marc Smith

NodeXL Network Server Frequently Asked Questions

The NodeXL team has released a new version (v.1.0.1.126) with better support for collecting data from social media network sources, starting with Twitter.  The NodeXL Network Server program now ships in every NodeXL installation.  Tony, the lead developer on the team, created the following FAQ to explain how to use the collector application.

This document describes how the NodeXL Network Server works.

  • What is the NodeXL Network Server?

It’s a Windows command-line program that downloads a network from Twitter and stores the network on disk in several file formats.  It can be run directly from a command line, but is typically scheduled to run on a periodic basis via the Task Scheduler that is built into Windows.

  • Where can the files be found?

The files are in NodeXL’s program folder.  To find out where the folder is, right-click the Microsoft NodeXL, Excel 2007 Template menu item in the Windows Start menu, then select Properties.  On 32-bit English computers, the folder is “C:\Program Files\Microsoft Research\Microsoft NodeXL Excel Template.”

  • Who are its intended users?

The Server is meant for use by people with moderate system administration skills.  It is not difficult to use, but it is not intended for the same audience as the NodeXL Excel Template, where ease of use is of high priority.

  • How do you run the Server from the Windows command line?

Like this:

NodeXLNetworkServer.exe NetworkConfiguration.xml

The program takes a single argument, which is the path to a configuration file that specifies which network should be downloaded and how the network should be saved to disk.  A particular configuration file might specify “Get the Twitter search network for people whose tweets contain ‘Sociology,’ add an edge for each ‘mentions’ relationship, limit to 100 people, include tweets, include statistics, and store the network as a GraphML file in the C:\NodeXLNetworks folder.”

The program immediately gets the requested network, saves it to disk, and exits.  On its own, it does not run on a periodic basis.

  • How do I create a configuration file?

You create a configuration file by copying a provided template file and editing the copy in Notepad.  The template file is named SampleNetworkConfiguration.xml and is stored in the same folder as the program.  The file is in XML format and the XML tags are clearly named and documented.

  • In what file formats can be the network be saved to disk?

You can save the network to either GraphML, which can be imported into a NodeXL workbook; directly to a NodeXL workbook; or both.

  • Do you typically run the program from the command line?

No.  Instead, you typically run it as a scheduled task via a built-in Windows program called Task Scheduler

Task Scheduler is a powerful utility that lets your run any program, including NodeXL Network Server, on a periodic basis.  You can, for example, tell Task Scheduler to run NodeXL Network Server using a particular network configuration file every twelve hours starting June 1, 2010 and ending June 30, 2010; or once a week starting now and continuing forever.  The scheduling options are endless.

  • Why not just include scheduling features in the NodeXL Network Server?

For two reasons.  First, Task Scheduler’s extensive scheduling options would be difficult to duplicate.  Second, if NodeXL Network Server had to download a network on a periodic basis, it would have to run as a Windows service, and Windows services are more complex to implement and to use than a simple command-line program.

  • How are the network files named?

Scheduling the NodeXL Network Server to run periodically can create any number of network files in the specified directory, so a file-naming scheme is needed.  The file name format is

{NetworkConfigFileName}_{Date}_{Time}.{Extension}.

So the above example, in which NetworkConfiguration.xml specifies that networks are to be saved as GraphML, might create a set of network files that look like this:

NetworkConfiguration_2010-06-01_02-00-00.graphml
NetworkConfiguration_2010-06-01_14-00-00. graphml
NetworkConfiguration_2010-06-02_02-00-00. graphml
…
  • What happens if the computer is not turned on at the scheduled time?

By default, the task won’t be performed until the next scheduled time when the computer is turned on.  However, if the computer is sleeping, you can tell Task Scheduler to wake it at the scheduled time to run the task.

  • What happens if the NodeXL Network Server encounters an error?

If the error prevents the network from being downloaded, the NodeXL Network Server creates an error file instead of a network file.  The file name starts with “Error” to make it easy to spot:

Error_NetworkConfiguration_2010-06-02_14-00-00.txt

The error file contains the details of what went wrong.

If one or more errors block part of the network but other parts of the network are successfully downloaded, then the NodeXL Network Server creates the network file containing the partial network, along with a text file that explains how many errors occurred.  The text file name starts with “PartialNetworkInfo” to make it easy to spot:

NetworkConfiguration_2010-06-02_14-00-00.Graphml
PartialNetworkInfo_NetworkConfiguration_Date.txt
  • What if I want to periodically download more than one network?

Simply schedule more than one task, each using a different network configuration file.  The tasks are independent of one another and can be scheduled to run at different times.

Posted in All posts, Metrics, Network data providers (spigots), NodeXL, Social Media, Social network, Twitter, User interface Tagged 2010, Chart, Data Collector, Desktop, Diagram, graph, GraphML, June, NodeXL, Server, SMRF, SMRFoundation, Social Media, Social Media Research Foundation, Twitter

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Apply NodeXL in espanol!

CÓMO ENCONTRAR LOS HASHTAGS MÁS POTENTES - Para convertir LEADS a VENTAS (SEOHashtag nº 1) (Spanish Edition)
By: Vivian Francos from #SEOHashtag Comparto algunas de las mejores formas de elegir los hashtags más poderosos y
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