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November

November 13 at 6pm: Data Community DC Workshop on Analyzing Social Media Networks using NodeXL

05NovMay 7, 2015 By Marc Smith

Data Community DC Logo

NodeXL Logo

I am excited to have the opportunity to present a NodeXL workshop at the DC Data Community on November 13th at 6pm in Washington, D.C.

In this session I will describe the ways NodeXL can simplify the process of collecting, storing, analyzing, visualizing and publishing reports about connected structures.

2013-SMRF-NodeXL-SNA-5 steps for Social Media Network Analysis

For example, this is a map of the connections among the people who recently tweeted about the DataCommunityDC Twitter account was created with just a few clicks and no coding:

DataCommunityDC Twitter NodeXL SNA Map and Report for Tuesday, 05 November 2013 at 15:15 UTC

This graph represents a network of 67 Twitter users whose recent tweets contained “DataCommunityDC“, taken from a data set limited to a maximum of 10,000 tweets. The network was obtained from Twitter on Tuesday, 05 November 2013 at 15:15 UTC.
The tweets in the network were tweeted over the 7-day, 16-hour, 4-minute period from Monday, 28 October 2013 at 22:38 UTC to Tuesday, 05 November 2013 at 14:42 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 network has been segmented into groups (“G1, G2, G3…”) and each group is labeled with the words most frequently used in the tweets from the people in that group.
The size of each Twitter user’s profile picture represents the log scaled value of their follower count.
Analysis of the network location of each participant reveals the people in key locations in the network, people at the “center” of the graph.

They are:

@datacommunitydc
@datafest2013
@gabosama
@harlanh
@mlh_holmes
@terebouza
@greglinch
@intridea
@gilpress
@katiestriff

The top URLs mentioned in this network were:

Continue reading →

Posted in 2013, All posts, Collective Action, Connected Action, Foundation, Industry, Measuring social media, Metrics, NodeXL, Presentation, Research, SMRF, SNA, Social Media, Social Media Research Foundation, Social network, Social Network Analysis, Social Roles, Social Theories and concepts, Sociology, Talk, Talks, Visualization, Workshop Tagged 2013, datacommunitydc, datacommunitydc.org, DC, NodeXL, November, SMRF, Social Media Research Foundation, Training, Tutorial, Washington, workshop

November 28 and 30: Mastering Social Media – Cape Town and Johannesburg, South Africa

18NovMay 7, 2015 By Marc Smith

Mastering Social Media 2011 is a workshop scheduled for November 28 and 30 in Cape Town and Johannesburg, South Africa.

My partner, Walter Pike, is a Marketing Maven and Founder of PiKE | New Marketing (www.pike.co.za) and the founder of the Digital Academy www.digitalacademy.co.za
He blogs at walterpike.com.

Mastering Social Media will give you practical tools on how to plan, execute and monitor your social media campaigns. Discussions will lead you through the introduction to social media marketing, understanding community dynamics, mapping social networks and applying network insights to your goals.
Brand Managers, Marketing Managers, Advertising Agencies, Digital Agencies, and PR Agencies are likely to find the day useful.

Venues and Dates

Cape Town

Protea Hotel Breakwater Lodge

28 November 2011
Protea Hotel
Breakwater Lodge,
Waterfront

Johannesburg

Gordon Institute of Business Science

30 November 2011
Gordon Institute
of Business Science,
Illovo

Pictures:

[flickrset id=”72157628305004757″ thumbnail=”thumbnail” photos=”” overlay=”false” size=”small”]

Posted in All posts, Conference, Connected Action, Measuring social media, Metrics, NodeXL, Research, Social Interaction, Social Media, Social network, Social Network Analysis, Sociology, Talks, Visualization Tagged 2011, Analysis, Cape Town, Chart, graph, Influencer, Map, Marc Smith, Marketing, network, NodeXL, November, Pretoria, SNA, Social Media, Social network, South Africa, Strategy, Visualization, Walter Pike, workshop

Contrasting teaparty and occupywallstreet twitter networks

16NovMay 7, 2015 By Marc Smith

Both teaparty and occupywallstreet are actively discussed in twitter.

This map of connections among people who tweeted Teaparty starts on 11/15/2011 14:22 UTC and ends on 11/15/2011 17:23, a total of 3 hours and 1 minute of traffic.

The Teaparty data set contained 1,533 tweets, replies and mentions.
Blue edges are connections created by replies and mentions. Grey lines are follows relationships.

Top most between users:
@ronpaul
@michellemalkin
@christopherhull
@theteaparty_net
@capaction
@thedailyedge
@bill1phd
@dbargen
@gulagbound
@rightcandidates

Graph Metric: Value
Graph Type: Directed
Vertices: 659
Unique Edges: 8808
Edges With Duplicates: 1423
Total Edges: 10231
Self-Loops: 1084
Connected Components: 49
Single-Vertex Connected Components: 44
Maximum Vertices in a Connected Component: 606
Maximum Edges in a Connected Component: 10148
Maximum Geodesic Distance (Diameter): 6
Average Geodesic Distance:2.693965
Graph Density: 0.02036797
NodeXL Version: 1.0.1.193

The major clusters are composed of teaparty supporters. The center bottom cluster are teaparty critics.

This map of the connections among people who tweeted Occupywallstreet starts on 11/15/2011 23:08 and ends on 11/15/2011 23:34 UTC, a total of 26 minutes of traffic.

Occupywallstreet 1,370 tweets, replies and mentions
Blue edges are connections created by replies and mentions. Grey lines are follows relationships.

Top most between users:
@occupywallst
@mmflint
@nyclu
@allisonkilkenny
@andrewbreitbart
@operationleaks
@occupydenver
@theatlantic
@usgeneralstrike
@rt_com

Graph Metric: Value
Graph Type: Directed
Vertices: 1000
Unique Edges: 3546
Edges With Duplicates: 826
Total Edges: 4372
Self-Loops: 794
Connected Components: 241
Single-Vertex Connected Components: 230
Maximum Vertices in a Connected Component: 747
Maximum Edges in a Connected Component: 3998
Maximum Geodesic Distance (Diameter): 7
Average Geodesic Distance: 2.65438
Graph Density: 0.003246246
NodeXL Version: 1.0.1.194

Some notable contrasts:
Teaparty Graph Density: 0.002652645
Occupywallstreet Graph Density: 0.02036797 – significantly lower levels of interconnection
Teaparty: Single-Vertex Connected Components 44 of 1000
Occupywallstreet: Single-Vertex Connected Components 283 of 1000

Many more “isolates” (Single-Vertex Connected Components) in Occupywallstreet.
Many more hubs, and more retweeting activity in Occupywallstreet.

The difference in duration of these data sets illustrates the relative speed of content creation in the topics. The data sets are commensurable in that they are both the result of a single query against the Twitter search API. So both maps are the results of charting connections among the authors of the last 1500 tweets, how ever long that takes to create.

Posted in All posts, Collective Action, Connected Action, Foundation, Measuring social media, Network clusters and communities, Network metrics and measures, Network visualization layouts, NodeXL, Politics, Research, Social Media, Social Media Research Foundation, Social network, Social Network Analysis, Social Roles, Sociology, Technology, Visualization Tagged #occupywallstreet, 15, 2011, Chart, graph, Information Visualization, Infovis, Map, network map, Networks, NodeXL, November, SNA, Social Media, teaparty, Visualization

Event: LocalSocialSummit11 and Social Media Research Foundation Reception November 10th, 2011

28OctMay 7, 2015 By Marc Smith

& 

On November 9th and 10th, 2011 the LocalSocialSummit11 will be held in London.

On Thursday morning, November 10th, Doctor Bernie Hogan from the Oxford Internet Institute and member of the Social Media Research Foundation will speak on the topic:

Insights: Social Network Analysis On Facebook Data, with a local twist

Thursday at 3:45 I will speak at the event on:

Charting Collections Of Connections In Social Media

Following the conference from 5 to 6pm will be a reception for the Social Media Research Foundation.

Please join us for refreshments and a discussion of the ways social media analysis tools can guide your engagement with stakeholders around the world.

The event is held at wallacespace:

22 Duke’s Road, London, WC1H 9PN
t +44(0)20 7395 1265
f +44 (0)20 7836 9591
e ask@wallacespace.com

22 Duke’s Road is only minutes walk away from Euston, St Pancras International, King’s Cross and Russell Square Tube.

Registration form for attending the event is below….
Continue reading →

Posted in All posts, Conference, Foundation, Measuring social media, NodeXL, Oxford, Research, SMRF, Social Media, Social Media Research Foundation, Social network, Talks, University, Visualization Tagged 2011, Chart, Event, graph, LocalSocialSummit, London, LSS, LSS11, Map, Mapping, NodeXL, November, Presentation, Reception, SMRF, Social Media, Social Media Research Foundation, Wallacespace

November 3, 2011: Seoul, South Korea – International Symposium on Convergence Technology (ConTech 2011)

22OctMay 7, 2015 By Marc Smith

I will speak at the International Symposium on Convergence Technology (ConTech 2011) – Smart & Humane World – on November 3rd in Seoul, South Korea.

Date: 2011 November 3 (Thurs)
Place: COEX Grand Ballroom, Seoul, Korea
Organized by Advanced Institutes of Convergence Technologies (AICT), Seoul National University (SNU)
In Cooperation with Ministry of Knowledge Economy, Ministry of Education, Science and Technology, National Research Foundation of Korea, Graduate School of Convergence Science and Technology (GSCST)
Symposium Chair : Choi, Yanghee (President, AICT)

Program
09:00~09:30 Registration
09:30~10:00 Opening Ceremony
Plenary Session : Smart & Humane World through Convergence
10:00~10:40 Speaker (TBD)
10:50~11:30 Speaker (TBD)
11:30~13:00 Lunch
Session 1 : Bio Convergence (Chair : Prof. Kim, Sunghoon)
Session 2 : IT Convergence (Chair : Dr. Lee, Manjai)
Session 3 : Appropriate Technology (Chair : Prof. Kang, Namjun)
13:00~15:00 Scott A. Strobel (Professor, Yale University)
Speaker Kevin Kim (Professor, University of Illinois)
Speaker Masaru Kitsuregawa (Professor, Tokyo University)
Speaker Haesun Park (Professor, Georgia Institute of Technology)
Speaker Marc Smith (Connected Action)
Speaker Sang-goo Lee (Professor, Seoul National University)
Speaker Haklae Kim (Samsung)
Speaker Raghu Ramakrishnan (Yahoo)

My slides: 20111103 con tech2011-marc smith

View more presentations from Marc Smith.

I will also visit Professor Han Woo Park at YeungNam University (Wikipedia) in Daegu, South Korea to meet with his students in the Webometrics Institute program.

This will be my second trip to Korea, I was there last year for a related event.  Pictures after the jump:

Continue reading →

Posted in All posts, Connected Action, Measuring social media, Mobile Social Software, NodeXL, Research, Social Media, Social network, Social Network Analysis, Talks, Visualization Tagged 2011, COEX, Conference, ConTech, ConTech2011, Korea, Marc, Marc Smith, network, NodeXL, November, Presentation, Smith, SNA, Social Media, South Korea, Talk, 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

A network guide to NodeXL features: The new NodeXL sample network (in v.159)

19DecMay 7, 2015 By Marc Smith

Eduarda Mendes Rodrigues, (University of Porto) from the NodeXL team has created a sample network file that attempts to highlight the functions and applications of the social media network analysis toolkit.  The latest release of NodeXL now contains this sample file:

In this map nodes represent the major feature groups and functions in the NodeXL application.

This map will become the default file that will open when you run NodeXL for the first time.  You will see a dialog like this:

Select Yes to have the graph above imported into the workbook.  You can then display the graph using the Show Graph button in the NodeXL menu ribbon.

After that, it will be available via the help menus. When you import the file, all of the data is also available in the spreadsheet part of NodeXL so that you can experiment with changing values there to see the impact in the graph display after you hit the “refresh graphs” button.

Over the coming weeks we plan to release additional sample network data sets that illustrate key concepts and methods in network science.  Suggestions for sample networks are welcome!

Posted in All posts, Foundation, Network data providers (spigots), Network metrics and measures, Network visualization layouts, NodeXL, SMRF, Social network, User interface, Visualization Tagged 2010, Analysis, Chart, graph, Hello, Map, network, November, Sample, SMRF, SMRFoundation, SNA, social, Social Media Research Foundation, Splash Screen, Visualization, World

Video: Panel Discussion from November 19: Using Social Media to Grow and Market Your Business

13DecMay 7, 2015 By Marc Smith

Video is now available from a panel hosted by the Women’s Affinity Group of O’Melveny & Myers’ Silicon Valley Office in Menlo Park on November 19th.  Along with Karla Spormann, President and CEO Tendo Communications, Martin Eberhard, Co-founder and former CEO Tesla Motors, Patrick Ewers, Founder, Mindmavin LLC.  We spoke about “Using Social Media to Grow and Market Your Business”.

We  discussed ways to leverage social networks  networks beyond personal connections – to provide business value.  We talked about ways to efficiently and effectively use social media to market and grow your business.

Using social media to grow and market your business
Using social media to grow and market your business

I spoke about tools, like NodeXL, that we have been building that create maps of the relationships among a population of people gathered by some shared attribute, like mentioning a keyword or hashtag.

Here are a few excerpts from the event created by Tendo Communications:

Posted in All posts, Measuring social media, NodeXL, Social Media, Social network, Talks Tagged 2009, Business, Connected Action, Marc Smith, Menlo Park, November, Panel, SNA, Social Media, Talk, Tendo, Video, Visualization, YouTube

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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

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Ines Mergel

Ways of Knowing in HCI

2014-Ways of Knowing in HCI - Olson and Kellogg

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

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