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SMRF

February 27, 2015 – Napa Area NodeXL Meetup – North Bay Networkers!

10FebMay 7, 2015 By Marc Smith

2015-Embassy Suites -NodeXL Meetup

Hello North Bay Area network analysis fans!

Join the NodeXL users meetup at the Napa Embassy Suites hotel (1075 California Boulevard, Napa, California, 94559, USA) on the 27th of February at 6pm.

Meet other network, social network, and social media network researchers and practitioners.

Hear about the latest and upcoming updates in the free and open NodeXL application.

Connect to the NodeXL network! Please RSVP using the form below:

[contact-form-7 404 "Not Found"]
Posted in 2015, All posts, Connected Action, Foundation, Measuring social media, NodeXL, Presentation, Session, SNA, Social Interaction, Social Media, Social Media Research Foundation, Social network, Social Network Analysis, Social Theories and concepts, Sociology, Talk, Talks, Training, Visualization, Workshop Tagged 2015, Analysis, Analytics, Connected Action, Foundation, Meeting, Napa, network, NodeXL, Research, SMRF, SNA, Social Media, Social Meida Research Foundation, User Group, Users

May 19-23, 2014: International Conference on Collaboration Technologies and Systems, Minneapolis, Minnesota

11MarMay 7, 2015 By Marc Smith
2014-CTS-Minneapolis Logo
Third International Symposium on
Collaboration, Social Computing, New Media and Networks
(SoMNet 2014)
Call for
Papers and Participation
As part of the
2014 International Conference on Collaboration Technologies and Systems
(CTS 2014)
May 19-23, 2014
The Commons Hotel
Minneapolis, Minnesota, USA
In Cooperation with
ACM, IEEE, and IFIP

 

Posted in 2014, All posts, Conference, CTS, Data Mining, Foundation, Measuring social media, Metrics, NodeXL, Research, Session, SMRF, Social Interaction, Social Media, Social Media Research Foundation, Social network, Social Network Analysis, Social Theories and concepts, Sociology, Talk, Talks, Training, Visualization, Workshop Tagged 2014, Conference, CTS, IEEE, Marc Smith, May, Minneapolis, SMRF, Social Media, Social Media Research Foundation, workshop

RADIO WVXU Cincinnati – Ann Thompson How millions of tweets boil down to six types of conversations

05MarMay 7, 2015 By Marc Smith

20140305-WVXU-Cincinnati-Pew-SMRF-6 Kinds of Twitter networks

RADIO WVXU Cincinnati – Ann Thompson interviews Marc Smith about the recent publication of a report on social media networks in Twitter co-authored with the Pew Internet Research Center.

“How millions of tweets boil down to six types of conversations“

http://www.connectedaction.net/wp-content/uploads/2014/03/20140305-WVXU-focus_PEW-SMRF-twitter_study-14.mp3

http://bit.ly/1eXt6IV  #NodeXL #SMRF #Pew #Network

Posted in 2014, All posts, Foundation, NodeXL, Pew Internet, Research, SMRF, SNA, Social Interaction, Social Media, Social Media Research Foundation, Social network, Social Network Analysis, Sociology, Talk, Talks, Visualization Tagged 2014, Ann Thompson, Cincinnati, NodeXL, Pew, SMRF, Social Media Research Foundation, WVXU

Social media network maps and reports covered in the press

05MarMay 7, 2015 By Marc Smith

Coverage of our report on the six basic types of social media network structures created with the Pew Internet Research Center has been extensive. Here is a round up of the articles we have found about the study.

20140314-OnTheMedia-Twitter Cartography-Lee Rainie

Lee Rainie, director of the Pew Internet Research Center was interviewed by Bob Garfield on OnTheMedia.
http://www.connectedaction.net/wp-content/uploads/2014/03/20140314-OnTheMedia-Twitter-Cartography-with-Lee-Rainie.mp3


20140220-WaPo-Pew-SMRF-6 Kinds of Twitter networks

Washington Post: The six types of conversations on Twitter


20140220-SFGate-Pew-SMRF-6 Kinds of Twitter networks

San Francisco Chronicle: The six ways we interact on Twitter


20140305-WVXU-Cincinnati-Pew-SMRF-6 Kinds of Twitter networks

http://www.connectedaction.net/wp-content/uploads/2014/03/20140305-WVXU-focus_PEW-SMRF-twitter_study-141.mp3

RADIO WVXU Cincinnati – Ann Thompson


20140228-MyFoxNY-Pew-SMRF-6 Kinds of Twitter networks

Fox News New York

 


20140220-AJAM-Pew-SMRF-6 Kinds of Twitter networks

Al Jazeera: Study maps Twitter’s information ecosystem

 


20140220-PBS Newshour Rundown-Pew-SMRF-6 Kinds of Twitter networks

PBS NewsHour: Study uncovers six basic types of Twitter conversations

 


20140220-DesMoines Register-Pew-SMRF-6 Kinds of Twitter networks

Des Moines Register: Twitter talk fits into 6 patterns, study finds

 


20140228-USAToday-Pew-SMRF-6 Kinds of Twitter networks

USAToday: Twitter talk fits into 6 patterns, study finds

 


20140220-NBCNews-Pew-SMRF-6 Kinds of Twitter networks

NBC: Liberals, Conservatives Tweet in Partisan Bubbles, Study Says

 


20140220-CNet-Pew-SMRF-6 Kinds of Twitter networks

CNET: Red state, blue state? On Twitter, never the twain shall meet

 


20140220-Time Entertainment-Pew-SMRF-6 Kinds of Twitter networks

TIME: Who Are TV’s Biggest Fans? New Research Names Twitter Users With the Most Influence

 


20140220-Quartz-Pew-SMRF-6 Kinds of Twitter networks

Quartz: Turns out Twitter is even more politically polarized than you thought

 


20140220-Forbes-Pew-SMRF-6 Kinds of Twitter networks

Forbes: These Charts Show Why Political Debate On Twitter Is Pointless

 


20140220-VatorNews-Pew-SMRF-6 Kinds of Twitter networks

Vator: Pew report: how we communicate on Twitter

 


20140220-GlobalNews CA-Pew-SMRF-6 Kinds of Twitter networks

Global News Canada: Study reveals six different types of conversations on Twitter

 


20140220-LiveScience-Pew-SMRF-6 Kinds of Twitter networks

Live Science: The 6 types of Twitter conversations revealed

 


20140220-SeattlePI-Pew-SMRF-6 Kinds of Twitter networks

Seattle PI: The six ways we interact on Twitter

 


20140220-AP-Pew-SMRF-6 Kinds of Twitter networks

Associated Press: Pew maps Twitter chatter in new type of study, finds 6 types of conversations

 


20140220-Redeye-Pew-SMRF-6 Kinds of Twitter networks

Chicago Tribune: The 5 cliques of Twitter

 


20140220-Mashable-Pew-SMRF-6 Kinds of Twitter networks

Mashable: Your Twitter Conversations Fall Into One of These Six Categories

 


20140220-PCMag-Pew-SMRF-6 Kinds of Twitter networks

PC Magazine: Which Type of Twitter Conversationalist Are You? In a recent report, Pew Researchers explain the six regularly observed types of conversation on Twitter

 


20140220-NPR-Pew-SMRF-6 Kinds of Twitter networks

NPR: Study: Conservatives And Liberals Rarely Debate On Twitter


20140220-DailyMail-Pew-SMRF-6 Kinds of Twitter networks

Daily Mail: What type of tweeter are you? Researchers reveal there are just SIX types of tweet

 


20140220-Diamondback-UMD-Pew-SMRF-6 Kinds of Twitter networks

The Diamond Back: Professor helps map social media connections

 


20140228-Forbes-Pew-SMRF-6 Kinds of Twitter networks

Your Social Media Conversation Is Like A Topographic Map

 


20140228-MediaPost-Pew-SMRF-6 Kinds of Twitter networks

Media Post

 


20140228-Politico-Pew-SMRF-6 Kinds of Twitter networks

Politico: How Twitter Works

 


20140228-UMD-Pew-SMRF-6 Kinds of Twitter networks

University of Maryland: New Map of Twitterverse finds 6 types of networks

 


20140228-UGA-Pew-SMRF-6 Kinds of Twitter networks

University of Georgia


2014-GovTech-6 Kinds of social media networks

GovTech


20140228-WiredIT-Pew-SMRF-6 Kinds of Twitter networks

Wired.IT


Posted in 2014, All posts, Foundation, NodeXL, Papers, Pew Internet, Research, SMRF, SNA, Social Interaction, Social Media, Social Media Research Foundation, Social network, Social Network Analysis, Social Roles, Sociology, Twitter Tagged 2014, 6 Types, Chart, graph, Information Visualization, Infovis, Map, network, NodeXL, Pew, Report, SMRF, Social Media, Social network, Social Structure, Twitter

Pew Internet and Social Media Research Foundation Report: Six kinds of social media networks in Twitter

20FebMay 7, 2015 By Marc Smith

2013-Pew Banner Logo

20110414-SMRF-Logo

NodeXL Logo

Working together,  the Pew Internet and American Life Project and the Social Media Research Foundation has published a report on the variations in social media crowd structures documented by network analysis and visualization of Twitter. The report is titled:

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.

2014-Pew-SMRF-NodeXL-6 Kinds of social media network patterns - Animated

The report was produced by Marc Smith from the Social Media Research Foundation, Lee Rainie from the Pew Research Center’s Internet & American Life Project, Itai Himelboim professor of communications at the University of Georgia, and Ben Shneiderman professor of computer science from the University of Maryland.

Posted in 2014, All posts, Collective Action, Companies, Connected Action, Foundation, Measuring social media, Metrics, NodeXL, Papers, Pew Internet, Politics, Research, SMRF, Social Interaction, Social Media, Social Media Research Foundation, Social network, Social Network Analysis, Twitter, University, Visualization Tagged American Life, Analysis, Ben Shneiderman, Big Data, Bigdata, Internet, Itai Himelboim, Lee Rainie, Marc Smith, network, network analysis, NodeXL, Pew, Political Network, Politics, SMRF, Social Media Research Foundation, Social Structure, Visualization

2014 INSNA Sunbelt SNA Conference: February 18-23 – St. Petersburg, Florida

03FebMay 7, 2015 By Marc Smith

2014-INSNA Sunbelt_logo

The INSNA Sunbelt social network conference will be held February 18-23 at the TradeWinds Island Resort on the island of St. Pete Beach.

There will be  NodeXL related talks at the conference.

NodeXL: Network Analysis Made Simple 
Tuesday February 18, 8:00am – 11:00am & 11:30am – 2:30pm

Marc Smith, Social Media Research Foundation
CITRUS Ballroom

Twitter Conversations as Network Structures: Typology and Measurements
Saturday February 22,

Itai Himelboim, Marc Smith, Ben Shneiderman, Lee Rainie

The conference schedule is available.

I hope to see you at the conference!

Posted in 2014, All posts, Collective Action, Common Goods, Community, Conference, Foundation, Measuring social media, Metrics, NodeXL, Papers, Presentation, Research, SMRF, SNA, Social Interaction, Social Media, Social Media Research Foundation, Social network, Social Network Analysis, Social Roles, Sociology, Sunbelt (INSNA), Talk, Talks, Visualization, Workshop Tagged 2014, Conference, INSNA, network, NodeXL, SMRF, Social Media Research Foundation, Sunbelt, Training, workshop 5 Comments

StrataConf 2014 – February 11-13, Santa Clara – Network Science Made Simple: SNA for pie chart makers

03FebMay 7, 2015 By Marc Smith

2014-strataconf_logo

I will present at the 2014 Strata Conference in Santa Clara, CA on February 11, 2013.

Network Science Made Simple: SNA for pie chart makers

Marc Smith (Connected Action Consulting Group)
2:20pm Wednesday, 02/12/2014
Data Science
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.

I will also hold Office Hours at the event:

Office Hour with Marc Smith (Team NodeXL)

Marc Smith (Connected Action Consulting Group)
3:00pm Wednesday, 02/12/2014
Office Hour
Table A
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:

  • @strataconf
  • @oreillymedia
  • @thedatacrunch
  • @dataiku
  • @alpinedatalabs
  • @sasanalytics
  • @zettaforce
  • @bigdata
  • @josemariasiota
  • @tibco

You can make these types of maps with just a few clicks using NodeXL.

I hope to see you in Santa Clara!

Strata Conference 2014

Posted in 2014, All posts, Collective Action, Conference, Connected Action, Data Mining, Foundation, Measuring social media, NodeXL, O'Reilly, Presentation, Research, SMRF, SNA, Social Interaction, Social Media, Social Media Research Foundation, Social network, Social Network Analysis, Social Roles, Social Theories and concepts, Sociology, Strata, Talk, Talks, Technology, Training, Visualization, Workshop Tagged 2014, Analysis, Lecture, network, network analysis, NodeXL, O'Reilly, SMRF, SNA, Social Media Research Foundation, Strata, StrataConf, Talk, Training, workshop 2 Comments

January 31, 2014 – Kansas State University – Webinar: Social Media Maps and Measures with NodeXL

16JanMay 7, 2015 By Marc Smith

2014-Kansas State University - Logo

I will present a remote seminar at Kansas State University – on Jan. 31 about how to create social media maps and measures with NodeXL.

The remote presentation will take place 1-2:30 p.m. (Central Time) Friday, Jan. 31, in 301 Hale Library.  All are welcome to attend.

See: https://blogs.k-state.edu/it-news/2014/01/10/webinar-jan-31-charting-collections-of-connections-in-social-media-creating-maps-and-measures-with-nodexl/

This is a map of the network of 2,785 Twitter users whose recent tweets contained ““kansas state” OR KState” over the 1-day, 23-hour, 14-minute period from Monday, 13 January 2014 at 17:06 UTC to Wednesday, 15 January 2014 at 16:20 UTC.

 

Posted in 2014, All posts, Conference, Foundation, Measuring social media, Metrics, NodeXL, Presentation, SMRF, Social Interaction, Social Media, Social Media Research Foundation, Social network, Social Network Analysis, Social Theories and concepts, Sociology, Talks, Technology, University, Video, Visualization, Workshop Tagged 2014, Infovis, January, Kansas, KSU, Marc Smith, network, NodeXL, Seminar, SMRF, SNA, Social Media, Social Media Research Foundation, Training, University, Webinar

University of Maryland Computer Science Class (CMSC734) Student Projects Put NodeXL to Work: Finding Insights in Diverse Networks

11DecMay 7, 2015 By Marc Smith

Screen Shot 2013-12-11 at 6.11.17 PM

NodeXL

Graduate students in Computer Science at the University of Maryland in a class on information visualization produced a striking variety of NodeXL network analysis visualizations for their recent homework projects.  The class, taught by Prof. Ben Shneiderman (www.cs.umd.edu/~ben), covers commercial tools, such as Spotfire and Tableau, and research software, giving students a chance to learn a range of existing visualization techniques and tools.  The NodeXL homework project is done by individual students, midway in the semester, while 5-person student teams are also busy working on their major term projects, which create novel visualization tools for specialized applications.  To see all the projects, click:

https://wiki.cs.umd.edu/cmsc734_f13/index.php?title=Homework_Number_2

(Don’t be deterred by security warnings, the class wiki is open for all to read, but only students can edit)!

Several of the 30 projects deal with Facebook, Twitter, email, Wikipedia, and YouTube social networks, with academic citation patterns and sports networks adding variety.  Entertainment, finance and medical analyses round out the collection, showing the huge range of potential NodeXL applications.  Students had only two weeks to find data, import it, clean it, and then create meaningful visualizations that enabled them to find interesting insights into connected structures.

Gregory Kramida’s analysis of stock symbol co-occurrences in financial articles

Gregory Kramida analyzed the connections among company names in the business press.  See:

https://wiki.cs.umd.edu/cmsc734_f13/images/9/9f/Analysis_of_Stock_Symbol_Co-occurences_in_Financial_Articles.pdf

The project shows the strong linkages between technology companies and consumer services, finance and public utilities.  The data set of more than 50,000  financial articles had more than 400,000 co-occurrences of stock ticker symbols.   He used the NodeXL grouping feature to organize the stocks into groups by industry and then showed results using the Group-in-a-Box layout feature.  This network is limited to companies that were mentioned together at least 50 times.

2013-UMD-CS-NodeXL-Kramida

Ruofei Du’s analysis of co-authorship patterns

Ruofei Du probed the relationship among authors in 1033 scientific papers from the 1988 to 2013 User Interface Software & Technology (UIST) conference. See:

https://wiki.cs.umd.edu/cmsc734_f13/images/b/bd/Uist_viz2.pdf

The co-author collaborations followed commonly seen patterns of professors and their students, but the relationships between academia and industry showed novel patterns.  After grouping authors by their organizations, it is apparent that Microsoft is well-represented at this conference through numerous collaborations with universities.

2013-UMD-CS-NodeXL-Du

Joshua Brule’s analysis of actor co-performance connections from the television series Firefly 

Joshua Brule created an intriguing story of television and film actors and actresses that emerges from analysis of ten actors from the cancelled television series Firefly. See:

https://wiki.cs.umd.edu/cmsc734_f13/images/7/76/Firefly.pdf

The actors had few collaborations before appearing on the program, but many afterwards.  The carefully constructed bipartite network shows how ten actors collaborated in 38 films, television shows, or videogames.

2013-UMD-CS-NodeXL-Brule

 

Posted in 2013, All posts, Foundation, Maryland, Metrics, NodeXL, Presentation, Research, SMRF, SNA, Social Media, Social Media Research Foundation, Social network, Social Network Analysis, Sociology, University, Visualization Tagged Analysis, CS, Maryland, network, NodeXL, Shneiderman, SMRF, SNA, Social Media Research Foundation, UMD, University, Visualization

Think link: network patterns in social media

24NovMay 7, 2015 By Marc Smith

2014-Pew-SMRF-NodeXL-6 Kinds of social media network patterns - Animated

Network analysis is a way of looking at the world that focuses on the shape and structure of collections of relationships.

In a network perspective the world is not primarily composed of individuals (“nodes”, “vertices”, “entities”). Instead, a network approach focuses on relationships between individuals (“edges”, “ties”, “connections”, “links”).

When collections of connections are analyzed, network patterns emerge. Networks have a variety of shapes and within them people occupy a variety of locations within each network. Some people are highly connected, while most people have just a few connections, for example.

Network theory provides a big collection of math that enables the measurement of these shapes and structures.

Using these measures, network analysis can identify key people in important locations in the network (for example: hubs, bridges, and islands). Network metrics allow for the network as a whole to be measured in terms of size and shape. Networks have many basic shapes and we have found six shapes to be common in internet and enterprise social media: divided, unified, fragmented, clustered, outward hub and spoke, inward hub and spoke. These shapes are created when people make individual decisions about who to reply to, link to, and like.

Divided networks are created when two groups of people talk about a controversial topic – but do not connect to people in the “other” group. Unified networks are formed by small to medium sized groups that are obscure or professional topics, conference hashtags are a good example. Fragmented networks have few connections among the people in them: these are often people talking about a brand or popular topic or event. Clusters sometimes grow among the people talking about a brand, indicating a existence of a brand “community”. Broadcast networks are formed when a prominent media person is widely repeated by many audience members, forming a hub-and-spoke pattern with the spokes pointed inward at the hub. The final pattern is the opposite, hub-and-spoke patterns with the hub linking out to a number of spokes. This pattern is generated by technical and customer support accounts like those for computer and airline companies. Additional patterns may exist, but these patterns are prominent in many social media network data sets.

When applied to external conversations, social media networks help identify the “mayor” of a hashtag or topic: these are the people at the center of the network. Network maps can be compared to the six basic types of networks to understand the nature of the topic community. We can look for examples of successful social media efforts and map those topic networks. Social media managers can contrast their topics with those of their aspirational targets and measure the difference between where they are and where they want to be.

When applied to enterprise conversations and connections, network analysis can reveal the experts who answer many people’s questions and “brokers” who bridge otherwise disconnected groups as well as the “structural holes” that show where a bridge or link is needed.

These insights can be useful in mergers, HR evaluation of group and manager performance, and identifying internal subject matter experts.

Research performed using NodeXL shows that work teams that have higher levels of internal connection (which is called “network density”) have higher levels of performance and profit. See:

The impact of intragroup social network topology on group performance: understanding intra-organizational knowledge transfer through a social capital framework
Wise, Sean Evan (2013) The impact of intragroup social network topology on group performance: understanding intra-organizational knowledge transfer through a social capital framework. PhD thesis, University of Glasgow.
Full text available as: PDF Download (2499Kb) | Preview
http://theses.gla.ac.uk/3793/

 

Posted in 2014, All posts, Data Mining, Foundation, Measuring social media, Metrics, NodeXL, Presentation, Research, SMRF, SNA, Social Media Research Foundation, Social network, Social Network Analysis, Social Roles, Social Theories and concepts, Sociology, Talks, Visualization Tagged Analysis, Data, graph, Motifs, network, NodeXL, Patterns, SMRF, SNA, Social Media, Social Media Research Foundation, Social network, Structures 1 Comment

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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

Networked


Networked By Lee Rainie and Barry Wellman

Social Media in the Public Sector

2015-07-31Social Media in the Public Sector-Cover
Ines Mergel

Ways of Knowing in HCI

2014-Ways of Knowing in HCI - Olson and Kellogg

The Virtual Community


Virtual Community

The Evolution of Cooperation


The Evolution of Cooperation

Governing the Commons


Governing the Commons

SmartMobs


SmartMobs

Networks, Crowds, and Markets


Networks, Crowds, and Markets

Development of Social Network Analysis


Development of Social Network Analysis: A Study in the Sociology of Science

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