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BI

Connected Action enables cloud storage of your social media networks with the NodeXL Graph Server Database

10FebMay 7, 2015 By Marc Smith

Connected Action Logo

Connected Action enables cloud storage of your NodeXL social media network datasets.

The Connected Action NodeXL Graph Server Importer allows you to import your Twitter or Facebook data into NodeXL from the cloud based Connected Action NodeXL Graph Database.

Contact Connected Action for pricing and availability.

The Connected Action NodeXL Graph Server Database enables NodeXL users to store their social media data from Twitter and Facebook in a personal Cloud Storage locker.

Specify the search terms and queries that matter to you with your Connected Action account representative and the Connected Action NodeXL Graph Database will collect and store your social media data for you every day.

Subscribers to the Connected Action NodeXL Graph Database can then use NodeXL to import long periods of their collected social media network data in a short period of time!

The importer can be added to any recent copy of NodeXL.

Just download and unzip the add-in and copy it to the folder you have selected to hold 3rd party importers for NodeXL .

You can select the folder to use for 3rd party importers via the NodeXL menu located at:

NodeXL>Data>Import>Import Options:

20150210-NodeXL-Data-Import-Import Options Dialog

This folder can be located anywhere in your file system.

When you restart NodeXL, your NodeXL>Data>Import Menu may look like this:

20150210-NodeXL-Data-Import-Import Menu List

When you select the option “From Connected Action NodeXL Graph Server…” you will get a dialog that looks like:

Enter  your account credentials and then enter the queries you have created with your Connected Action account representative.

NodeXL will then import a social media network data set that can be automatically analyzed and visualized.

Posted in 2015, All posts, Connected Action NodeXL Graph Server Importer, Measuring social media, Metrics, Network clusters and communities, Network Data Archives, Network data providers (spigots), Network metrics and measures, NodeXL, SNA, Social Interaction, Social Media, Social network, Social Network Analysis, Social Theories and concepts, Sociology, Technology, Visualization, Web Application Tagged 2015, Add-in, Analytics, BI, Cloud, Comments, Connected Action, Facebook, Fan Pages, Feature, Groups, Importer, Likes, Locker, network, NodeXL, Pages, Posts, Product, Service, SNA, Social network, socialmedia, Tweets

November 17-18, 2014: Cape Town South Africa: MammothBI Conference – talk about social media networks

25OctMay 7, 2015 By Marc Smith

2014-mammothbi_logo

I am delighted to return to South Africa where I will participate in the Mammoth BI conference in Cape Town, on November 17-18, 2014 at the Cape Town International Conference Centre, Convention Square, 1 Lower Long Street, Cape Town, 8001, Western Cape, South Africa.

2014-mammothbi_speakers

Posted in 2014, All posts, Companies, Conference, Connected Action, Foundation, Measuring social media, NodeXL, Presentation, Research, SNA, Social Media, Social Media Research Foundation, Social network, Social Network Analysis, Social Theories and concepts, Sociology, Talks, Technology, Visualization, Workshop Tagged 2014, Analytics, BI, Conference, Event, Mammoth, Marc Smith, NodeXL, SNA, Social Media, South Africa

April 12, 2013 PASS Business Analytics Conference: Mapping social media with NodeXL

06MarMay 7, 2015 By Marc Smith

 

 2013-PASSBAC Square   I will speak at the 2013 PASS Business Analytics Conference in Chicago on April 12, 2013.  The event focuses on data discovery, data exploration and visualization, predictive analytics, content management and architecture, collaboration, information strategies, and more.  I will speak about social media Data Analytics and Visualization in a presentation titled: Charting Collections of Social Media Connections with NodeXL. 
 network of 106 Twitter users whose recent tweets contained
This is a sample NodeXL graph that represents a network of 106 Twitter users whose recent tweets contained “passbac”. The network was obtained on Wednesday, 30 January 2013 at 01:09 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 tweets were made over the 7-day, 5-hour, 32-minute period from Tuesday, 22 January 2013 at 17:40 UTC to Tuesday, 29 January 2013 at 23:12 UTC.

 Learn to make your own network maps of social media at PASSBAC 2013!

2013-passbac_web_banner

Posted in All posts, Conference, Foundation, Industry, Network metrics and measures, Network visualization layouts, NodeXL, PASSBAC, Research, SMRF, SNA, Social Interaction, Social Media, Social Media Research Foundation, Social network, Social Network Analysis, Social Theories and concepts, Talks, Visualization Tagged 2013, Analytics, April, BI, Business Intelligence, Chicago, Conference, Data Analysis, Lecture, Marc Smith, NodeXL, PASSBAC, Predictive Analytics, SQL, Talk, workshop 1 Comment

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

Posted in All posts, Companies, Conference, Connected Action, Foundation, Measuring social media, Metrics, Network clusters and communities, Network Data Archives, Network data providers (spigots), Network metrics and measures, Network visualization layouts, NodeXL, SMRF, Social Media, Social Media Research Foundation, Social network, Social Network Analysis, Sociology, Talks, User interface, Visualization, Web Application Tagged 2011, Analysis, BI, Chart, Event, graph, Map, Marc Smith, Measure, network, New York, NodeXL, NYC, October, PAW, Predictive Analytics World, Presentation, SNA, Social Media, Social network, Talk, Visualization

#JW11 NodeXL SNA Map for 10 October 2011

11OctMay 7, 2015 By Marc Smith

The Jive World 11 conference took place October 4-6, 2011.

[flickr id=”6234653454″ thumbnail=”medium” overlay=”true” size=”large” group=”” align=”none”]
These are the connections among the Twitter users who recently tweeted the word #JW11 when queried on October 10, 2011, scaled by numbers of followers (with outliers thresholded). Connections created when users reply, mention or follow one another.

See: www.jivesoftware.com/jiveworld

A larger version of the image is here: www.flickr.com/photos/marc_smith/6234653454/sizes/l/in/ph…

Top most between users:
@jivesoftware
@gialyons
@mikefraietta
@cflanagan
@cosmopolitan_lv
@ginorossi
@kristinhersant
@thebrandbuilder
@alanlepo
@mor_trisha

Graph Metric: Value
Graph Type: Directed
Vertices: 345
Unique Edges: 3606
Edges With Duplicates: 2072
Total Edges: 5678
Self-Loops: 632
Connected Components: 11
Single-Vertex Connected Components: 9
Maximum Vertices in a Connected Component: 334
Maximum Edges in a Connected Component: 5659
Maximum Geodesic Distance (Diameter): 5
Average Geodesic Distance: 2.353001
Graph Density: 0.034184361
NodeXL Version: 1.0.1.179

More NodeXL network visualizations are here: www.flickr.com/photos/marc_smith/sets/72157622437066929/

Posted in All posts, Conference, Industry, Measuring social media, Network visualization layouts, NodeXL, Social Media, Social Network Analysis, Social Roles, Sociology, Visualization Tagged 2011, Analysis, Analytics, BI, Conference, EventGraph, Infovis, Jive, network analysis, NodeXL, October, Platform, SNA, Social Media, Social network, Social Software, socialmedia, Twitter

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Transparency in Social Media

2015-07-30-Transparency in Social Media-Structures of Twitter Crowds and COnversations
Transparency in Social Media
Sorin Adam Matei, Martha G. Russell, Elisa Bertino

CÓMO ENCONTRAR LOS HASHTAGS MÁS POTENTES: Para convertir LEADS a VENTAS (SEOHashtag nº 1) (Spanish Edition)

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
que puedan generar tráfico a tus redes sociales para aprovechar el poder del
hashtag.
Si quieres aumentar tus interacciones, debes aprender a utilizar los hashtags como herramienta.

https://amzn.to/305Hpsv

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Networked By Lee Rainie and Barry Wellman

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2014-Ways of Knowing in HCI - Olson and Kellogg

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Networks, Crowds, and Markets


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