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Pew Internet

Radio: OnTheMedia – Twitter Cartography – with Lee Rainie from Pew Internet

15MarMay 7, 2015 By Marc Smith

20140314-OnTheMedia-Twitter Cartography-Lee Rainie

Lee Rainie, director of the Pew Internet Research Center was interviewed by Bob Garfield on OnTheMedia this week about the recently released report on mapping Twitter topic networks.  The report found six distinct patterns of social media networks in Twitter: divided, unified, fragmented, clustered, and in and out hub and spoke patterns. They discuss the prospects for overcoming polarization in social media and the hopeful signs that many other forms of social network structures exist in addition to the divided network pattern.

http://www.connectedaction.net/wp-content/uploads/2014/03/20140314-OnTheMedia-Twitter-Cartography-with-Lee-Rainie.mp3
Posted in 2014, All posts, Measuring social media, NodeXL, Pew Internet, Presentation, Research, SMRF, Social Interaction, Social Media, Social Media Research Foundation, Social Network Analysis, Social Theories and concepts, Sociology, Talk, Talks, Visualization Tagged 2014, Audio, Chart, graph, Image, Interview, Lee Rainie, Map, March, network, NPR, OnTheMedia, Pew, Pew Internet, Podcast, Radio, Research, SNA, Social Media, Twitter

April 1, 2014 – NodeXL SNA of social media talk at Federal Big Data Working Group

06MarMay 7, 2015 By Marc Smith

2014-Federal Big Data Working Group-Banner

I will present a talk about social media network at the April 1st Federal Big Data Working Group at 6:30pm.

Talk details are on the SemanticCommunity.info site.

The Federal Big Data Working Group supports the Federal Big Data Initiative and the Federal Digital Government Strategy.

See: http://www.meetup.com/Federal-Big-Data-Working-Group/

The talk will focus on the easy to follow steps needed to create social media network maps and reports automatically from services like Twitter, Facebook, YouTube, Flickr, email, blogs, wikis, and the WWW.  Here is a sample network map of the term #bigdataprivacy:

The graph represents a network of 248 Twitter users whose recent tweets contained “#bigdataprivacy”, or who were replied to or mentioned in those tweets. The tweets in the network were tweeted over the 6-day, 10-hour, 29-minute period from Tuesday, 25 February 2014 at 14:36 UTC to Tuesday, 04 March 2014 at 01:06 UTC.  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 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:
@whitehouseostp, @mit, @mit_csail, @steve_lockstep, @aureliepols, @dbarthjones, @digiphile, @stannenb, @djweitzner, @mikaelf

Top URLs in Tweet in Entire Graph:
http://web.mit.edu/bigdata-priv/webcast.html
http://www.commerce.gov/news/secretary-speeches/2014/03/03/us-secretary-commerce-penny-pritzker-delivers-remarks-mit
http://web.mit.edu/bigdata-priv/agenda.html
http://www.whitehouse.gov/blog/2014/02/24/privacy-workshop-explore-big-data-opportunities-challenges
http://www.nytimes.com/glogin?mobile=1&URI=http%3A%2F%2Fmobile.nytimes.com%2F2014%2F03%2F03%2Ftechnology%2Fwhen-start-ups-dont-lock-the-doors.html
http://www.techrepublic.com/article/privacy-concerns-about-data-collection-may-lead-to-dumbing-down-smart-devices/
http://m.technologyreview.com/news/525131/intel-designs-a-safe-meeting-place-for-private-data/
http://thedatamap.org
http://www.foreignaffairs.com/articles/140741/craig-mundie/privacy-pragmatism
http://www.cs.ucdavis.edu/~franklin/ecs289/2010/dwork_2008.pdf

Posted in 2014, All posts, Conference, Foundation, Measuring social media, Metrics, NodeXL, Pew Internet, Presentation, Research, Session, SMRF, SNA, Social Interaction, Social Media, Social Media Research Foundation, Social network, Social Network Analysis, Social Roles, Social Theories and concepts, Sociology, Talks, Visualization Tagged 2014, April, Big Data, Chart, Federal, graph, Map, Marc Smith, network, NodeXL, SNA, Social network, Visualization

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

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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

Social Media in the Public Sector

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2014-Ways of Knowing in HCI - Olson and Kellogg

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