6 slides about SMRF

Marc A. SmithChief Social ScientistConnected Action Consulting Groupmarc@connectedaction.nethttp://www.connectedaction.nethttp://nodexl.codeplex.com/A project from the Social Media Research Foundation: http://www.smrfoundation.orgMapping and Measuring Connections

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About MeIntroductions

Marc A. SmithChief Social ScientistConnected Action Consulting Group

Marc@connectedaction.nethttp://www.connectedaction.nethttp://www.codeplex.com/nodexlhttp://www.twitter.com/marc_smithhttp://www.flickr.com/photos/marc_smithhttp://www.facebook.com/marc.smith.sociologisthttp://www.linkedin.com/in/marcasmithhttp://www.slideshare.net/Marc_A_Smithhttp://www.smrfoundation.org

Central tenet Social structure emerges from the aggregate of relationships (ties) among members of a populationPhenomena of interestEmergence of cliques and clusters from patterns of relationshipsCentrality (core), periphery (isolates), betweennessMethodsSurveys, interviews, observations, log file analysis, computational analysis of matrices

(Hampton &Wellman, 1999; Paolillo, 2001; Wellman, 2001)Source: Richards, W. (1986). The NEGOPY network analysis program. Burnaby, BC: Department of Communication, Simon Fraser University. pp.7-16

Social Network Theoryhttp://en.wikipedia.org/wiki/Social_network

CSCW 2004 - Analyzing Social CMC3

SNA 101Nodeactor on which relationships act; 1-mode versus 2-mode networksEdgeRelationship connecting nodes; can be directionalCohesive Sub-GroupWell-connected group; clique; clusterKey MetricsCentrality (group or individual measure)Number of direct connections that individuals have with others in the group (usually look at incoming connections only)Measure at the individual node or group levelCohesion (group measure)Ease with which a network can connectAggregate measure of shortest path between each node pair at network level reflects average distanceDensity (group measure)Robustness of the networkNumber of connections that exist in the group out of 100% possible Betweenness (individual measure)# shortest paths between each node pair that a node is onMeasure at the individual node levelNode rolesPeripheral below average centralityCentral connector above average centralityBroker above average betweenness

EDFACBHGICDEABDE

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OF

Crowds matter

Kodak BrownieSnap-Shot Camera

The first easy to use point and shoot!

http://www.browniecamera.nl/brownie_original_model.htmhttp://en.wikipedia.org/wiki/Snapshot_%28photography%29

http://www.flickr.com/photos/amycgx/3119640267/

Crowds

http://www.flickr.com/photos/amycgx/3119640267/8

Social Media (email, Facebook, Twitter, YouTube, and more) is all about connections

from people

to people.10

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Patterns are left behind11

11I can look at the tracks people have left behind in their interactions with me.

There are many kinds of ties. Send, Mention, http://www.flickr.com/photos/stevendepolo/3254238329Like, Link, Reply, Rate, Review, Favorite, Friend, Follow, Forward, Edit, Tag, Comment, Check-in Internet Verbs!

Think LinkNodes & Edges

Is related to

ABIs related toIs related to

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Think LinkNodes & Edges

Is related to

ABIs related toIs related to

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World Wide WebSocial media must contain one or more social networks

Vertex1Vertex 2Edge AttributeVertex1 AttributeVertex2 Attribute@UserName1@UserName2valuevaluevalue

A network is born whenever two GUIDs are joined.

UsernameAttributes@UserName1Value, value

UsernameAttributes@UserName2Value, value

AB

NodeXL imports edges from social media data sources

Location, Location, Location

Position, Position, Position

Mapping and Measuring Connections with

Like MSPaint for graphs. the Community

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Now Available

Communities in Cyberspace

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What we are trying to do:Open Tools, Open Data, Open ScholarshipBuild the Firefox of GraphML open tools for collecting and visualizing social media dataConnect users to network analysis make network charts as easy as making a pie chartConnect researchers to social media data sourcesArchive: Be the Allen Very Large Telescope Array for Social Media data coordinate and aggregate the results of many users data collection and analysisCreate open access research papers & findingsMake collections of connections easy for users to manage

Goal: Make SNA easierExisting Social Network Tools are challenging for many novice usersTools like Excel are widely usedLeveraging a spreadsheet as a host for SNA lowers barriers to network data analysis and display

What we have done: Open ToolsNodeXLData providers (spigots)ThreadMill Message BoardExchange Enterprise EmailVoson HyperlinkSharePointFacebookTwitterYouTubeFlickr

NodeXL Ribbon in Excel

What we have done: Open DataNodeXLGraphGallery.orgUser generated collection of network graphs, datasets and annotationsCollective repository for the research communityPublished collections of data from a range of social media data sources to help students and researchers connect with data of interest and relevance

What we have done: Open Scholarship

http://www.pewinternet.org/2014/02/20/mapping-twitter-topic-networks-from-polarized-crowds-to-community-clusters/

http://www.pewinternet.org/2014/02/20/mapping-twitter-topic-networks-from-polarized-crowds-to-community-clusters/30

Network Analysis Data Flow

PublicationVisualizationAnalysisContainerProviders

http://www.flickr.com/photos/badgopher/3264760070/Data Providers

http://www.flickr.com/photos/badgopher/3264760070/

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Providers

Example NodeXL data importer for Twitter

http://www.flickr.com/photos/druclimb/2212572259/in/photostream/Data Container

Container

Data Analysishttp://www.flickr.com/photos/hchalkley/47839243/

Analysis

Data Visualizationhttp://www.flickr.com/photos/rvwithtito/4236716778

Visualization

http://www.flickr.com/photos/62693815@N03/6277208708/Data Publication

Publication

Social Network Maps Reveal

Key influencers in any topic.

Sub-groups.

Bridges.

Hubs

Bridges

Islandshttp://www.flickr.com/photos/storm-crypt/3047698741

http://www.flickr.com/photos/library_of_congress/3295494976/sizes/o/in/photostream/Clusters

http://www.flickr.com/photos/library_of_congress/3295494976/sizes/o/in/photostream/47

[Divided]Polarized Crowds[Unified]Tight Crowd[Fragmented]Brand Clusters[Clustered]Community Clusters[In-Hub & Spoke]Broadcast Network[Out-Hub & Spoke]Support Network

6 kinds of Twitter social media networks

[Divided]Polarized Crowds[Unified]Tight Crowd[Fragmented]Brand Clusters[Clustered]Community Clusters[In-Hub & Spoke]Broadcast Network[Out-Hub & Spoke]Support Network

6 kinds of Twitter social media networks

#My2KPolarized

The network of connections among people who tweeted #My2K over the 1-day, 21-hour, 39-minute period from Sunday, 06 January 2013 at 03:30 UTC to Tuesday, 08 January 2013 at 01:09 UTC. 50

#CMgrChatIn-group / Community

The graph represents a network of 268 Twitter users whose recent tweets contained "#cmgrchat OR #smchat. The network was obtained on Friday, 18 January 2013 at 15:44 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 3-day, 21-hour, 15-minute period from Monday, 14 January 2013 at 18:23 UTC to Friday, 18 January 2013 at 15:38 UTC.51

LumiaBrand / Public Topic

The graph represents a network of 1,227 Twitter users whose recent tweets contained "lumia. The network was obtained on Saturday, 12 January 2013 at 19:52 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 5-hour, 1-minute period from Saturday, 12 January 2013 at 14:36 UTC to Saturday, 12 January 2013 at 19:37 UTC.52

#FLOTUSBazaar

The graph represents a network of 1,260 Twitter users whose recent tweets contained "flotus". The network was obtained on Friday, 18 January 2013 at 18:26 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 3-hour, 3-minute period from Friday, 18 January 2013 at 15:16 UTC to Friday, 18 January 2013 at 18:20 UTC.53

New York Times ArticlePaul KrugmanBroadcast: Audience + Communities

The graph represents a network of 399 Twitter users whose recent tweets contained "http://www.nytimes.com/2013/01/11/opinion/krugman-coins-against-crazies.html. The network was obtained on Friday, 11 January 2013 at 14:27 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 12-hour, 32-minute period from Friday, 11 January 2013 at 01:52 UTC to Friday, 11 January 2013 at 14:24 UTC.54

Dell Listens/DellcaresSupport

The graph represents a network of 388 Twitter users whose recent tweets contained "delllistens OR dellcares. The network was obtained on Tuesday, 19 February 2013 at 17:44 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 6-day, 21-hour, 58-minute period from Tuesday, 12 February 2013 at 19:34 UTC to Tuesday, 19 February 2013 at 17:33 UTC.55

SNA questions for social media:

What does my topic network look like?What does the topic I aspire to be look like?What is the difference between #1 and #2?How does my map change as I intervene?

What does #YourHashtag look like?

Top 10 Vertices@tnwconference@shingy@aral@patrick@jarnoduursma@sarahmarshall@boris@briansolis@technifista@qadabraplatform

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Most central:@bitpay@coindesk@tuurdemeester@bitgiveorg@allthingsbtc@ihavebitcoins@btcmarketsnews@sp0rkyd0rky@hermetec@redditbtc

strataconf Twitter NodeXL SNA Map and Report for 2014-02-11 12-53-27

Top 10 Vertices, Ranked by Betweenness Centrality:@strataconf@peteskomoroch@acroll@oreillymedia@orthonormalruss@ayirpelle@bigdata@furrier@marketpowerplus@sassoftware

https://www.nodexlgraphgallery.org/Pages/Graph.aspx?graphID=16540

strataconf Twitter NodeXL SNA Map and Report for 2014-02-11 12-53-27

The graph represents a network of 1,685 Twitter users whose recent tweets contained "strataconf",tweeted over the 8-day, 0-hour, 44-minute period from Monday, 03 February 2014 at 19:55 UTC to Tuesday, 11 February 2014 at 20:39 UTC.

Top Hashtags in Tweet in Entire Graph: #Strataconf, #bigdata, #hds, #BigDataSV, #hadoop, #ddbd60

datavis Twitter NodeXL SNA Map and Report for Tuesday, 11 February 2014 at 18:55 UTC

Top 10 Vertices, Ranked by Betweenness Centrality:@bigpupazzoverde@randal_olson@twitterdata@7of13@yochum@edwardtufte@twittersports@grandjeanmartin@smfrogers@albertocairo

https://www.nodexlgraphgallery.org/Pages/Graph.aspx?graphID=16541

datavis Twitter NodeXL SNA Map and Report for Tuesday, 11 February 2014 at 18:55 UTC

The graph represents a network of Twitter users whose tweets in the requested date range contained "dataviz OR datavis over the 41-day, 4-hour, 5-minute period from Wednesday, 01 January 2014 at 00:01 UTC to Tuesday, 11 February 2014 at 04:06 UTC

Top Hashtags in Tweet in Entire Graph: #dataviz, #bigdata, #analytics, #map, #Europe, #Datavis, #Audit, #Logs

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[Divided]Polarized Crowds[Unified]Tight Crowd[Fragmented]Brand Clusters[Clustered]Community Clusters[In-Hub & Spoke]Broadcast Network[Out-Hub & Spoke]Support Network

6 kinds of Twitter social media networks

[Divided]Polarized Crowds[Unified]Tight Crowd[Fragmented]Brand Clusters[Clustered]Communities[In-Hub & Spoke]Broadcast Network[Out-Hub & Spoke]Support Network

[Low probability]Find bridge users.Encourage shared material.[Low probability]Get message out to disconnected communities.[Possible transition]Draw in new participants.[Possible transition]Regularly create content.[Possible transition]Reply to multiple users.

[Undesirable transition]Remove bridges, highlight divisions.[Low probability]Get message out to disconnected communities.[High probability]Draw in new participants.[Possible transition]Regularly create content.[Possible transition]Reply to multiple users.

[Undesirable transition]Increase density of connections in two groups.[Low probability]Dramatically increase density of connections.[High probability]Increase retention, build connections.[Possible transition]Regularly create content.[Possible transition]Reply to multiple users.

[Undesirable transition]Increase density of connections in two groups.[Low probability]Dramatically increase density of connections.[Undesirable transition]Increase population, reduce connections.[Possible transition]Regularly create content.[Possible transition]Reply to multiple users.

[Undesirable transition]Increase density of connections in two groups.[Low probability]Dramatically increase density of connections.[Low probability]Get message out to disconnected communities.[Possible transition]Increase retention, build connections.[High probability]Increase reply rate, reply to multiple users.

[Undesirable transition]Increase density of connections in two groups.[Low probability]Dramatically increase density of connections.[Possible transition]Get message out to disconnected communities.[High probability]Increase retention, build connections.[High probability]Increase publication of new content and regularly create content.

Red=Undesireable transitionYellow=Low probability transitionLight blue= potential transition or complementary structureDark green = strong transition or complementary structure

http://www.katypearce.net/protestbaku-analysis-the-day-after/64

C. Scott Dempwolf, PhDResearch Assistant Professor & DirectorUMD - Morgan State Center for Economic Development

http://portal.sliderocket.com/ATWBE/Using-SNA-to-find-and-manage-RICs

C. Scott Dempwolf, PhDResearch Assistant Professor & DirectorUMD - Morgan State Center for Economic Development

http://www.terpconnect.umd.edu/~dempy/

Insights: many clusters are based around a county and local enterprises. E.g., the middle-left cluster is Pittsburgh metro area, with large orange Westinghouse Electric. The Philadelphia cluster in the top-right is highly connected to the bottom left, which are adjacent counties. An exception to location grouping is the top-left pharma and medical cluster, composed of several companies, universities, HHS, and an interesting arrangement of inventors in several connected fans.https://plus.google.com/photos/116499393494903612852/albums/5659635437858992593/5659734868308985794?banner=pwa&pid=5659734868308985794&oid=11649939349490361285265

What is Social Network Analysis? How is it useful for the humanities?1. New framework for analysis2. Data visualization allows new perspectives less linear, more comprehensiveSocial Network Analysis and Ancient HistoryDiane H. Cline, Ph.D.University of Cincinnati

Prof. Diane Clinehttp://www.academia.edu/2153390/The_Social_network_of_Alexander_the_Great_Social_Network_Analysis_in_Ancient_History

Its about who you know, and who those people know, and how everyone knows each other.Data visualization tool to see data differently.66

Strategies for social media engagement based on social media network analysis

Request your own network map and report

http://connectedaction.net

What we want to do: (Build the tools to) map the social webMove NodeXL to the web: (Node[NOT]XL)Node for Google Doc Spreadsheets? WebGL Canvas? D3.JS? Sigma.JSConnect to more data sources of interest:RDF, MediaWikis, Gmail, NYT, Citation NetworksSolve hard network manipulation UI problems:Modal transform, Time series, Automated layoutsGrow and maintain archives of social media network data sets for research use.Improve network science education:Workshops on social media network analysisLive lectures and presentationsVideos and training materials

How you can helpSponsor a featureSponsor workshopsSponsor a studentSchedule trainingSponsor the foundationDonate your money, code, computation, storage, bandwidth, data or employees timeHelp promote the work of the Social Media Research Foundation

Thank you!

Marc A. SmithChief Social ScientistConnected Action Consulting Groupmarc@connectedaction.nethttp://www.connectedaction.nethttp://nodexl.codeplex.com/A project from the Social Media Research Foundation: http://www.smrfoundation.orgMapping and Measuring Connections

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